Interspeech
Collection
Accepted papers for Interspeech (Annual Conference of the International Speech Communication Association), one dataset per year. • 13 items • Updated
paper_id stringlengths 15 32 | title stringlengths 22 188 | authors listlengths 1 20 | isca_url stringlengths 66 83 | pdf_url stringlengths 65 82 | doi stringlengths 30 30 | pages stringlengths 3 9 | bibtex large_stringlengths 291 739 | abstract large_stringlengths 411 1.7k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values |
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wu19_interspeech | Advances in Automatic Speech Recognition for Child Speech Using Factored Time Delay Neural Network | [
"Fei Wu",
"Leibny Paola GarcÃa-Perera",
"Daniel Povey",
"Sanjeev Khudanpur"
] | https://www.isca-archive.org/interspeech_2019/wu19_interspeech.html | https://www.isca-archive.org/interspeech_2019/wu19_interspeech.pdf | 10.21437/Interspeech.2019-2980 | 1-5 | @inproceedings{wu19_interspeech,
title = {{Advances in Automatic Speech Recognition for Child Speech Using Factored Time Delay Neural Network}},
author = {Fei Wu and Leibny Paola GarcÃa-Perera and Daniel Povey and Sanjeev Khudanpur},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {1... | Automatic speech recognition (ASR) has shown huge advances in adult
speech; however, when the models are tested on child speech, the performance
does not achieve satisfactory word error rates (WER). This is mainly
due to the high variance in acoustic features of child speech and the
lack of clean, labeled corpora. We a... | null | null |
yeung19_interspeech | A Frequency Normalization Technique for Kindergarten Speech Recognition Inspired by the Role of f in Vowel Perception | [
"Gary Yeung",
"Abeer Alwan"
] | https://www.isca-archive.org/interspeech_2019/yeung19_interspeech.html | https://www.isca-archive.org/interspeech_2019/yeung19_interspeech.pdf | 10.21437/Interspeech.2019-1847 | 6-10 | @inproceedings{yeung19_interspeech,
title = {{A Frequency Normalization Technique for Kindergarten Speech Recognition Inspired by the Role of fo in Vowel Perception}},
author = {Gary Yeung and Abeer Alwan},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {6--10},
doi = {10.214... | Accurate automatic speech recognition (ASR) of kindergarten speech
is particularly important as this age group may benefit the most from
voice-based educational tools. Due to the lack of young child speech
data, kindergarten ASR systems often are trained using older child
or adult speech. This study proposes a fundamen... | null | null |
gale19_interspeech | Improving ASR Systems for Children with Autism and Language Impairment Using Domain-Focused DNN Transfer Techniques | [
"Robert Gale",
"Liu Chen",
"Jill Dolata",
"Jan van Santen",
"Meysam Asgari"
] | https://www.isca-archive.org/interspeech_2019/gale19_interspeech.html | https://www.isca-archive.org/interspeech_2019/gale19_interspeech.pdf | 10.21437/Interspeech.2019-3161 | 11-15 | @inproceedings{gale19_interspeech,
title = {{Improving ASR Systems for Children with Autism and Language Impairment Using Domain-Focused DNN Transfer Techniques}},
author = {Robert Gale and Liu Chen and Jill Dolata and Jan van Santen and Meysam Asgari},
year = {2019},
booktitle = {{Interspeech 2019}... | This study explores building and improving an automatic speech recognition
(ASR) system for children aged 6–9 years and diagnosed with autism
spectrum disorder (ASD), language impairment (LI), or both. Working
with only 1.5 hours of target data in which children perform the Clinical
Evaluation of Language Fundamentals ... | null | null |
ribeiro19_interspeech | Ultrasound Tongue Imaging for Diarization and Alignment of Child Speech Therapy Sessions | [
"Manuel Sam Ribeiro",
"Aciel Eshky",
"Korin Richmond",
"Steve Renals"
] | https://www.isca-archive.org/interspeech_2019/ribeiro19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ribeiro19_interspeech.pdf | 10.21437/Interspeech.2019-2612 | 16-20 | @inproceedings{ribeiro19_interspeech,
title = {{Ultrasound Tongue Imaging for Diarization and Alignment of Child Speech Therapy Sessions}},
author = {Manuel Sam Ribeiro and Aciel Eshky and Korin Richmond and Steve Renals},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {16--20},
do... | We investigate the automatic processing of child speech therapy sessions
using ultrasound visual biofeedback, with a specific focus on complementing
acoustic features with ultrasound images of the tongue for the tasks
of speaker diarization and time-alignment of target words. For speaker
diarization, we propose an ultr... | 1907.00818 | title_snapshot |
loukina19_interspeech | Automated Estimation of Oral Reading Fluency During Summer Camp e-Book Reading with MyTurnToRead | [
"Anastassia Loukina",
"Beata Beigman Klebanov",
"Patrick Lange",
"Yao Qian",
"Binod Gyawali",
"Nitin Madnani",
"Abhinav Misra",
"Klaus Zechner",
"Zuowei Wang",
"John Sabatini"
] | https://www.isca-archive.org/interspeech_2019/loukina19_interspeech.html | https://www.isca-archive.org/interspeech_2019/loukina19_interspeech.pdf | 10.21437/Interspeech.2019-2889 | 21-25 | @inproceedings{loukina19_interspeech,
title = {{Automated Estimation of Oral Reading Fluency During Summer Camp e-Book Reading with MyTurnToRead}},
author = {Anastassia Loukina and Beata Beigman Klebanov and Patrick Lange and Yao Qian and Binod Gyawali and Nitin Madnani and Abhinav Misra and Klaus Zechner an... | Use of speech technologies in the classroom is often limited by the
inferior acoustic conditions as well as other factors that might affect
the quality of the recordings. We describe MyTurnToRead, an e-book-based
app designed to support an interleaved listening and reading experience,
where the child takes turns readin... | null | null |
lopes19_interspeech | Sustained Vowel Game: A Computer Therapy Game for Children with Dysphonia | [
"Vanessa Lopes",
"João Magalhães",
"Sofia Cavaco"
] | https://www.isca-archive.org/interspeech_2019/lopes19_interspeech.html | https://www.isca-archive.org/interspeech_2019/lopes19_interspeech.pdf | 10.21437/Interspeech.2019-3017 | 26-30 | @inproceedings{lopes19_interspeech,
title = {{Sustained Vowel Game: A Computer Therapy Game for Children with Dysphonia}},
author = {Vanessa Lopes and João Magalhães and Sofia Cavaco},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {26--30},
doi = {10.21437/Interspeech.2019... | Problems in vocal quality are common in 4 to 12-year-old children,
which may affect their health as well as their social interactions
and development process. The sustained vowel exercise is widely used
by speech and language pathologists for the child’s voice recovery
and vocal re-education. Nonetheless, despite being... | null | null |
esposito19_interspeech | The Dependability of Voice on Elders’ Acceptance of Humanoid Agents | [
"Anna Esposito",
"Terry Amorese",
"Marialucia Cuciniello",
"Maria Teresa Riviello",
"Antonietta M. Esposito",
"Alda Troncone",
"Gennaro Cordasco"
] | https://www.isca-archive.org/interspeech_2019/esposito19_interspeech.html | https://www.isca-archive.org/interspeech_2019/esposito19_interspeech.pdf | 10.21437/Interspeech.2019-1734 | 31-35 | @inproceedings{esposito19_interspeech,
title = {{The Dependability of Voice on Elders’ Acceptance of Humanoid Agents}},
author = {Anna Esposito and Terry Amorese and Marialucia Cuciniello and Maria Teresa Riviello and Antonietta M. Esposito and Alda Troncone and Gennaro Cordasco},
year = {2019},
boo... | The research on ambient assistive technology is concerned with features
humanoid agents should show in order to gain user acceptance. However,
differently aged groups may have different requirements. This paper
is particularly focused on agent’s voice preferences among elders,
young adults, and adolescents. To this aim... | null | null |
niebuhr19_interspeech | God as Interlocutor — Real or Imaginary? Prosodic Markers of Dialogue Speech and Expected Efficacy in Spoken Prayer | [
"Oliver Niebuhr",
"Uffe Schjoedt"
] | https://www.isca-archive.org/interspeech_2019/niebuhr19_interspeech.html | https://www.isca-archive.org/interspeech_2019/niebuhr19_interspeech.pdf | 10.21437/Interspeech.2019-1193 | 36-40 | @inproceedings{niebuhr19_interspeech,
title = {{God as Interlocutor — Real or Imaginary? Prosodic Markers of Dialogue Speech and Expected Efficacy in Spoken Prayer}},
author = {Oliver Niebuhr and Uffe Schjoedt},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {36--40},
doi = {... | We analyze the phonetic correlates of petitionary prayer in 22 Christian
practitioners. Our aim is to examine if praying is characterized by
prosodic markers of dialogue speech and expected efficacy. Three similar
conditions are compared; 1) requests to God, 2) requests to a human
recipient, 3) requests to an imaginary... | null | null |
cohn19_interspeech | Expressiveness Influences Human Vocal Alignment Toward voice-AI | [
"Michelle Cohn",
"Georgia Zellou"
] | https://www.isca-archive.org/interspeech_2019/cohn19_interspeech.html | https://www.isca-archive.org/interspeech_2019/cohn19_interspeech.pdf | 10.21437/Interspeech.2019-1368 | 41-45 | @inproceedings{cohn19_interspeech,
title = {{Expressiveness Influences Human Vocal Alignment Toward voice-AI}},
author = {Michelle Cohn and Georgia Zellou},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {41--45},
doi = {10.21437/Interspeech.2019-1368},
issn = {2958-17... | This study explores whether people align to expressive speech spoken
by a voice-activated artificially intelligent device (voice-AI), specifically
Amazon’s Alexa. Participants shadowed words produced by the Alexa
voice in two acoustically distinct conditions: “regular”
and “expressive”, containing more exaggerated pitc... | null | null |
lai19_interspeech | Detecting Topic-Oriented Speaker Stance in Conversational Speech | [
"Catherine Lai",
"Beatrice Alex",
"Johanna D. Moore",
"Leimin Tian",
"Tatsuro Hori",
"Gianpiero Francesca"
] | https://www.isca-archive.org/interspeech_2019/lai19_interspeech.html | https://www.isca-archive.org/interspeech_2019/lai19_interspeech.pdf | 10.21437/Interspeech.2019-2632 | 46-50 | @inproceedings{lai19_interspeech,
title = {{Detecting Topic-Oriented Speaker Stance in Conversational Speech}},
author = {Catherine Lai and Beatrice Alex and Johanna D. Moore and Leimin Tian and Tatsuro Hori and Gianpiero Francesca},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {46... | Being able to detect topics and speaker stances in conversations is
a key requirement for developing spoken language understanding systems
that are personalized and adaptive. In this work, we explore how topic-oriented
speaker stance is expressed in conversational speech. To do this, we
present a new set of topic and s... | null | null |
sebastian19_interspeech | Fusion Techniques for Utterance-Level Emotion Recognition Combining Speech and Transcripts | [
"Jilt Sebastian",
"Piero Pierucci"
] | https://www.isca-archive.org/interspeech_2019/sebastian19_interspeech.html | https://www.isca-archive.org/interspeech_2019/sebastian19_interspeech.pdf | 10.21437/Interspeech.2019-3201 | 51-55 | @inproceedings{sebastian19_interspeech,
title = {{Fusion Techniques for Utterance-Level Emotion Recognition Combining Speech and Transcripts}},
author = {Jilt Sebastian and Piero Pierucci},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {51--55},
doi = {10.21437/Interspeech.2... | In human perception and understanding, a number of different and complementary
cues are adopted according to different modalities. Various emotional
states in communication between humans reflect this variety of cues
across modalities. Recent developments in multi-modal emotion recognition
utilize deep-learning techniq... | null | null |
rajwadi19_interspeech | Explaining Sentiment Classification | [
"Marvin Rajwadi",
"Cornelius Glackin",
"Julie Wall",
"Gérard Chollet",
"Nigel Cannings"
] | https://www.isca-archive.org/interspeech_2019/rajwadi19_interspeech.html | https://www.isca-archive.org/interspeech_2019/rajwadi19_interspeech.pdf | 10.21437/Interspeech.2019-2743 | 56-60 | @inproceedings{rajwadi19_interspeech,
title = {{Explaining Sentiment Classification}},
author = {Marvin Rajwadi and Cornelius Glackin and Julie Wall and Gérard Chollet and Nigel Cannings},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {56--60},
doi = {10.21437/Interspeech.2... | This paper presents a novel 1-D sentiment classifier trained on the
benchmark IMDB dataset. The classifier is a 1-D convolutional neural
network with repeated convolution and max pooling layers. The main
contribution of this work is the demonstration of a deconvolution technique
for 1-D convolutional neural networks th... | null | null |
kleinlein19_interspeech | Predicting Group-Level Skin Attention to Short Movies from Audio-Based LSTM-Mixture of Experts Models | [
"Ricardo Kleinlein",
"Cristina Luna Jiménez",
"Juan Manuel Montero",
"Zoraida Callejas",
"Fernando Fernández-MartÃnez"
] | https://www.isca-archive.org/interspeech_2019/kleinlein19_interspeech.html | https://www.isca-archive.org/interspeech_2019/kleinlein19_interspeech.pdf | 10.21437/Interspeech.2019-2799 | 61-65 | @inproceedings{kleinlein19_interspeech,
title = {{Predicting Group-Level Skin Attention to Short Movies from Audio-Based LSTM-Mixture of Experts Models}},
author = {Ricardo Kleinlein and Cristina Luna Jiménez and Juan Manuel Montero and Zoraida Callejas and Fernando Fernández-MartÃnez},
year = {201... | Electrodermal activity (EDA) is a psychophysiological indicator that
can be considered a somatic marker of the emotional and attentional
reaction of subjects towards stimuli like audiovisual content. EDA
measurements are not biased by the cognitive process of giving an opinion
or a score to characterize the subjective ... | null | null |
pham19_interspeech | Very Deep Self-Attention Networks for End-to-End Speech Recognition | [
"Ngoc-Quan Pham",
"Thai-Son Nguyen",
"Jan Niehues",
"Markus Müller",
"Alex Waibel"
] | https://www.isca-archive.org/interspeech_2019/pham19_interspeech.html | https://www.isca-archive.org/interspeech_2019/pham19_interspeech.pdf | 10.21437/Interspeech.2019-2702 | 66-70 | @inproceedings{pham19_interspeech,
title = {{Very Deep Self-Attention Networks for End-to-End Speech Recognition}},
author = {Ngoc-Quan Pham and Thai-Son Nguyen and Jan Niehues and Markus Müller and Alex Waibel},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {66--70},
doi =... | Recently, end-to-end sequence-to-sequence models for speech recognition
have gained significant interest in the research community. While previous
architecture choices revolve around time-delay neural networks (TDNN)
and long short-term memory (LSTM) recurrent neural networks, we propose
to use self-attention via the T... | 1904.13377 | title_snapshot |
li19_interspeech | Jasper: An End-to-End Convolutional Neural Acoustic Model | [
"Jason Li",
"Vitaly Lavrukhin",
"Boris Ginsburg",
"Ryan Leary",
"Oleksii Kuchaiev",
"Jonathan M. Cohen",
"Huyen Nguyen",
"Ravi Teja Gadde"
] | https://www.isca-archive.org/interspeech_2019/li19_interspeech.html | https://www.isca-archive.org/interspeech_2019/li19_interspeech.pdf | 10.21437/Interspeech.2019-1819 | 71-75 | @inproceedings{li19_interspeech,
title = {{Jasper: An End-to-End Convolutional Neural Acoustic Model}},
author = {Jason Li and Vitaly Lavrukhin and Boris Ginsburg and Ryan Leary and Oleksii Kuchaiev and Jonathan M. Cohen and Huyen Nguyen and Ravi Teja Gadde},
year = {2019},
booktitle = {{Interspeech... | In this paper we report state-of-the-art results on LibriSpeech among
end-to-end speech recognition models without any external training
data. Our model, Jasper, uses only 1D convolutions, batch normalization,
ReLU, dropout, and residual connections. To improve training, we further
introduce a new layer-wise optimizer ... | 1904.03288 | title_snapshot |
moritz19_interspeech | Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition | [
"Niko Moritz",
"Takaaki Hori",
"Jonathan Le Roux"
] | https://www.isca-archive.org/interspeech_2019/moritz19_interspeech.html | https://www.isca-archive.org/interspeech_2019/moritz19_interspeech.pdf | 10.21437/Interspeech.2019-2837 | 76-80 | @inproceedings{moritz19_interspeech,
title = {{Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition}},
author = {Niko Moritz and Takaaki Hori and Jonathan Le Roux},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {76--80},
doi = {10.21437/Int... | In hybrid automatic speech recognition (ASR) systems, neural networks
are used as acoustic models (AMs) to recognize phonemes that are composed
to words and sentences using pronunciation dictionaries, hidden Markov
models, and language models, which can be jointly represented by a
weighted finite state transducer (WFST... | null | null |
belinkov19_interspeech | Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition | [
"Yonatan Belinkov",
"Ahmed Ali",
"James Glass"
] | https://www.isca-archive.org/interspeech_2019/belinkov19_interspeech.html | https://www.isca-archive.org/interspeech_2019/belinkov19_interspeech.pdf | 10.21437/Interspeech.2019-2599 | 81-85 | @inproceedings{belinkov19_interspeech,
title = {{Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition}},
author = {Yonatan Belinkov and Ahmed Ali and James Glass},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {81--85},
doi = {10.21437/... | End-to-end neural network systems for automatic speech recognition
(ASR) are trained from acoustic features to text transcriptions. In
contrast to modular ASR systems, which contain separately-trained components
for acoustic modeling, pronunciation lexicon, and language modeling,
the end-to-end paradigm is both concept... | 1907.04224 | title_snapshot |
tawara19_interspeech | Multi-Channel Speech Enhancement Using Time-Domain Convolutional Denoising Autoencoder | [
"Naohiro Tawara",
"Tetsunori Kobayashi",
"Tetsuji Ogawa"
] | https://www.isca-archive.org/interspeech_2019/tawara19_interspeech.html | https://www.isca-archive.org/interspeech_2019/tawara19_interspeech.pdf | 10.21437/Interspeech.2019-3197 | 86-90 | @inproceedings{tawara19_interspeech,
title = {{Multi-Channel Speech Enhancement Using Time-Domain Convolutional Denoising Autoencoder}},
author = {Naohiro Tawara and Tetsunori Kobayashi and Tetsuji Ogawa},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {86--90},
doi = {10.214... | This paper investigates the use of time-domain convolutional denoising
autoencoders (TCDAEs) with multiple channels as a method of speech
enhancement. In general, denoising autoencoders (DAEs), deep learning
systems that map noise-corrupted into clean waveforms, have been shown
to generate high-quality signals while wo... | null | null |
tesch19_interspeech | On Nonlinear Spatial Filtering in Multichannel Speech Enhancement | [
"Kristina Tesch",
"Robert Rehr",
"Timo Gerkmann"
] | https://www.isca-archive.org/interspeech_2019/tesch19_interspeech.html | https://www.isca-archive.org/interspeech_2019/tesch19_interspeech.pdf | 10.21437/Interspeech.2019-2751 | 91-95 | @inproceedings{tesch19_interspeech,
title = {{On Nonlinear Spatial Filtering in Multichannel Speech Enhancement}},
author = {Kristina Tesch and Robert Rehr and Timo Gerkmann},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {91--95},
doi = {10.21437/Interspeech.2019-2751},
i... | Using multiple microphones for speech enhancement allows for exploiting
spatial information for improved performance. In most cases, the spatial
filter is selected to be a linear function of the input as, for example,
the minimum variance distortionless response (MVDR) beamformer. For
non-Gaussian distributed noise, ho... | null | null |
martindonas19_interspeech | Multi-Channel Block-Online Source Extraction Based on Utterance Adaptation | [
"Juan M. MartÃn-Doñas",
"Jens Heitkaemper",
"Reinhold Haeb-Umbach",
"Angel M. Gomez",
"Antonio M. Peinado"
] | https://www.isca-archive.org/interspeech_2019/martindonas19_interspeech.html | https://www.isca-archive.org/interspeech_2019/martindonas19_interspeech.pdf | 10.21437/Interspeech.2019-2244 | 96-100 | @inproceedings{martindonas19_interspeech,
title = {{Multi-Channel Block-Online Source Extraction Based on Utterance Adaptation}},
author = {Juan M. MartÃn-Doñas and Jens Heitkaemper and Reinhold Haeb-Umbach and Angel M. Gomez and Antonio M. Peinado},
year = {2019},
booktitle = {{Interspeech 2019}}... | This paper deals with multi-channel speech recognition in scenarios
with multiple speakers. Recently, the spectral characteristics of a
target speaker, extracted from an adaptation utterance, have been used
to guide a neural network mask estimator to focus on that speaker.
In this work we present two variants of speake... | null | null |
bagheri19_interspeech | Exploiting Multi-Channel Speech Presence Probability in Parametric Multi-Channel Wiener Filter | [
"Saeed Bagheri",
"Daniele Giacobello"
] | https://www.isca-archive.org/interspeech_2019/bagheri19_interspeech.html | https://www.isca-archive.org/interspeech_2019/bagheri19_interspeech.pdf | 10.21437/Interspeech.2019-2665 | 101-105 | @inproceedings{bagheri19_interspeech,
title = {{Exploiting Multi-Channel Speech Presence Probability in Parametric Multi-Channel Wiener Filter}},
author = {Saeed Bagheri and Daniele Giacobello},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {101--105},
doi = {10.21437/Inters... | In this paper, we present a practical implementation of the parametric
multi-channel Wiener filter (PMWF) noise reduction algorithm. In particular,
we extend on methods that incorporate the multi-channel speech presence
probability (MC-SPP) in the PMWF derivation and its output. The use
of the MC-SPP brings several adv... | null | null |
togami19_interspeech | Variational Bayesian Multi-Channel Speech Dereverberation Under Noisy Environments with Probabilistic Convolutive Transfer Function | [
"Masahito Togami",
"Tatsuya Komatsu"
] | https://www.isca-archive.org/interspeech_2019/togami19_interspeech.html | https://www.isca-archive.org/interspeech_2019/togami19_interspeech.pdf | 10.21437/Interspeech.2019-1220 | 106-110 | @inproceedings{togami19_interspeech,
title = {{Variational Bayesian Multi-Channel Speech Dereverberation Under Noisy Environments with Probabilistic Convolutive Transfer Function}},
author = {Masahito Togami and Tatsuya Komatsu},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {106--1... | In this paper, we propose a multi-channel speech dereverberation method
which can reduce reverberation even when acoustic transfer functions
(ATFs) are time varying under noisy environments. The microphone input
signal is modeled as a convolutive mixture in a time-frequency domain
so as to incorporate late reverberatio... | null | null |
nakatani19_interspeech | Simultaneous Denoising and Dereverberation for Low-Latency Applications Using Frame-by-Frame Online Unified Convolutional Beamformer | [
"Tomohiro Nakatani",
"Keisuke Kinoshita"
] | https://www.isca-archive.org/interspeech_2019/nakatani19_interspeech.html | https://www.isca-archive.org/interspeech_2019/nakatani19_interspeech.pdf | 10.21437/Interspeech.2019-1286 | 111-115 | @inproceedings{nakatani19_interspeech,
title = {{Simultaneous Denoising and Dereverberation for Low-Latency Applications Using Frame-by-Frame Online Unified Convolutional Beamformer}},
author = {Tomohiro Nakatani and Keisuke Kinoshita},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = ... | This article presents frame-by-frame online processing algorithms for
a Weighted Power minimization Distortionless response convolutional
beamformer (WPD). The WPD unifies widely-used multichannel dereverberation
and denoising methods, namely a weighted prediction error based dereverberation
method (WPE) and a minimum ... | null | null |
snyder19_interspeech | Individual Variation in Cognitive Processing Style Predicts Differences in Phonetic Imitation of Device and Human Voices | [
"Cathryn Snyder",
"Michelle Cohn",
"Georgia Zellou"
] | https://www.isca-archive.org/interspeech_2019/snyder19_interspeech.html | https://www.isca-archive.org/interspeech_2019/snyder19_interspeech.pdf | 10.21437/Interspeech.2019-2669 | 116-120 | @inproceedings{snyder19_interspeech,
title = {{Individual Variation in Cognitive Processing Style Predicts Differences in Phonetic Imitation of Device and Human Voices}},
author = {Cathryn Snyder and Michelle Cohn and Georgia Zellou},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {1... | Phonetic imitation, or implicitly matching the acoustic-phonetic patterns
of another speaker, has been empirically associated with natural tendencies
to promote successful social communication, as well as individual differences
in personality and cognitive processing style. The present study explores
whether individual... | null | null |
illa19_interspeech | An Investigation on Speaker Specific Articulatory Synthesis with Speaker Independent Articulatory Inversion | [
"Aravind Illa",
"Prasanta Kumar Ghosh"
] | https://www.isca-archive.org/interspeech_2019/illa19_interspeech.html | https://www.isca-archive.org/interspeech_2019/illa19_interspeech.pdf | 10.21437/Interspeech.2019-2664 | 121-125 | @inproceedings{illa19_interspeech,
title = {{An Investigation on Speaker Specific Articulatory Synthesis with Speaker Independent Articulatory Inversion}},
author = {Aravind Illa and Prasanta Kumar Ghosh},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {121--125},
doi = {10.2... | Estimating speech representations from articulatory movements is known
as articulatory-to-acoustic forward (AAF) mapping. Typically this mapping
is learned using directly measured articulatory movement in a subject-specific
manner. Such AAF mapping has been shown to benefit the speech synthesis
applications. In this wo... | null | null |
zhang19_interspeech | Individual Difference of Relative Tongue Size and its Acoustic Effects | [
"Xiaohan Zhang",
"Chongke Bi",
"Kiyoshi Honda",
"Wenhuan Lu",
"Jianguo Wei"
] | https://www.isca-archive.org/interspeech_2019/zhang19_interspeech.html | https://www.isca-archive.org/interspeech_2019/zhang19_interspeech.pdf | 10.21437/Interspeech.2019-2452 | 126-130 | @inproceedings{zhang19_interspeech,
title = {{Individual Difference of Relative Tongue Size and its Acoustic Effects}},
author = {Xiaohan Zhang and Chongke Bi and Kiyoshi Honda and Wenhuan Lu and Jianguo Wei},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {126--130},
doi = {... | This study examines how the speaker’s tongue size contributes
to generating dynamic characteristics of speaker individuality. The
relative tongue size (RTS) has been proposed as an index for the tongue
area within the oropharyngeal cavity on the midsagittal magnetic resonance
imaging (MRI). Our earlier studies have sho... | null | null |
yoshinaga19_interspeech | Individual Differences of Airflow and Sound Generation in the Vocal Tract of Sibilant /s/ | [
"Tsukasa Yoshinaga",
"Kazunori Nozaki",
"Shigeo Wada"
] | https://www.isca-archive.org/interspeech_2019/yoshinaga19_interspeech.html | https://www.isca-archive.org/interspeech_2019/yoshinaga19_interspeech.pdf | 10.21437/Interspeech.2019-1376 | 131-135 | @inproceedings{yoshinaga19_interspeech,
title = {{Individual Differences of Airflow and Sound Generation in the Vocal Tract of Sibilant /s/}},
author = {Tsukasa Yoshinaga and Kazunori Nozaki and Shigeo Wada},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {131--135},
doi = {1... | To clarify the individual differences of flow and sound characteristics
of sibilant /s/, the large eddy simulation of compressible flow was
applied to vocal tract geometries of five subjects pronouncing /s/.
The vocal tract geometry was extracted by separately collecting images
of digital dental casts and the vocal tra... | null | null |
uttam19_interspeech | Hush-Hush Speak: Speech Reconstruction Using Silent Videos | [
"Shashwat Uttam",
"Yaman Kumar",
"Dhruva Sahrawat",
"Mansi Aggarwal",
"Rajiv Ratn Shah",
"Debanjan Mahata",
"Amanda Stent"
] | https://www.isca-archive.org/interspeech_2019/uttam19_interspeech.html | https://www.isca-archive.org/interspeech_2019/uttam19_interspeech.pdf | 10.21437/Interspeech.2019-3269 | 136-140 | @inproceedings{uttam19_interspeech,
title = {{Hush-Hush Speak: Speech Reconstruction Using Silent Videos}},
author = {Shashwat Uttam and Yaman Kumar and Dhruva Sahrawat and Mansi Aggarwal and Rajiv Ratn Shah and Debanjan Mahata and Amanda Stent},
year = {2019},
booktitle = {{Interspeech 2019}},
pa... | Speech Reconstruction is the task of recreation of speech using silent
videos as input. In the literature, it is also referred to as lipreading.
In this paper, we design an encoder-decoder architecture which takes
silent videos as input and outputs an audio spectrogram of the reconstructed
speech. The model, despite b... | null | null |
saha19_interspeech | SPEAK YOUR MIND! Towards Imagined Speech Recognition with Hierarchical Deep Learning | [
"Pramit Saha",
"Muhammad Abdul-Mageed",
"Sidney Fels"
] | https://www.isca-archive.org/interspeech_2019/saha19_interspeech.html | https://www.isca-archive.org/interspeech_2019/saha19_interspeech.pdf | 10.21437/Interspeech.2019-3041 | 141-145 | @inproceedings{saha19_interspeech,
title = {{SPEAK YOUR MIND! Towards Imagined Speech Recognition with Hierarchical Deep Learning}},
author = {Pramit Saha and Muhammad Abdul-Mageed and Sidney Fels},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {141--145},
doi = {10.21437/In... | Speech-related Brain Computer Interface (BCI) technologies provide
effective vocal communication strategies for controlling devices through
speech commands interpreted from brain signals. In order to infer imagined
speech from active thoughts, we propose a novel hierarchical deep learning
BCI system for subject-indepen... | 1904.05746 | title_snapshot |
chung19_interspeech | An Unsupervised Autoregressive Model for Speech Representation Learning | [
"Yu-An Chung",
"Wei-Ning Hsu",
"Hao Tang",
"James Glass"
] | https://www.isca-archive.org/interspeech_2019/chung19_interspeech.html | https://www.isca-archive.org/interspeech_2019/chung19_interspeech.pdf | 10.21437/Interspeech.2019-1473 | 146-150 | @inproceedings{chung19_interspeech,
title = {{An Unsupervised Autoregressive Model for Speech Representation Learning}},
author = {Yu-An Chung and Wei-Ning Hsu and Hao Tang and James Glass},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {146--150},
doi = {10.21437/Interspeec... | This paper proposes a novel unsupervised autoregressive neural model
for learning generic speech representations. In contrast to other speech
representation learning methods that aim to remove noise or speaker
variabilities, ours is designed to preserve information for a wide
range of downstream tasks. In addition, the... | 1904.03240 | title_snapshot |
huang19_interspeech | Harmonic-Aligned Frame Mask Based on Non-Stationary Gabor Transform with Application to Content-Dependent Speaker Comparison | [
"Feng Huang",
"Peter Balazs"
] | https://www.isca-archive.org/interspeech_2019/huang19_interspeech.html | https://www.isca-archive.org/interspeech_2019/huang19_interspeech.pdf | 10.21437/Interspeech.2019-1327 | 151-155 | @inproceedings{huang19_interspeech,
title = {{Harmonic-Aligned Frame Mask Based on Non-Stationary Gabor Transform with Application to Content-Dependent Speaker Comparison}},
author = {Feng Huang and Peter Balazs},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {151--155},
doi ... | We propose harmonic-aligned frame mask for speech signals using non-stationary
Gabor transform (NSGT). A frame mask operates on the transfer coefficients
of a signal and consequently converts the signal into a counterpart
signal. It depicts the difference between the two signals. In preceding
studies, frame masks based... | 1904.10380 | title_snapshot |
m19_interspeech | Glottal Closure Instants Detection from Speech Signal by Deep Features Extracted from Raw Speech and Linear Prediction Residual | [
"Gurunath Reddy M.",
"K. Sreenivasa Rao",
"Partha Pratim Das"
] | https://www.isca-archive.org/interspeech_2019/m19_interspeech.html | https://www.isca-archive.org/interspeech_2019/m19_interspeech.pdf | 10.21437/Interspeech.2019-1981 | 156-160 | @inproceedings{m19_interspeech,
title = {{Glottal Closure Instants Detection from Speech Signal by Deep Features Extracted from Raw Speech and Linear Prediction Residual}},
author = {Gurunath Reddy M. and K. Sreenivasa Rao and Partha Pratim Das},
year = {2019},
booktitle = {{Interspeech 2019}},
pa... | Glottal closure instants (GCI) also called as instants of significant
excitation occur during abrupt closure of vocal folds is a well-studied
problem for its many potential applications in speech processing. Speech
signal or its transformed linear prediction residual (LPR) is the most
popular signal representations for... | null | null |
pascual19_interspeech | Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks | [
"Santiago Pascual",
"Mirco Ravanelli",
"Joan SerrÃ",
"Antonio Bonafonte",
"Yoshua Bengio"
] | https://www.isca-archive.org/interspeech_2019/pascual19_interspeech.html | https://www.isca-archive.org/interspeech_2019/pascual19_interspeech.pdf | 10.21437/Interspeech.2019-2605 | 161-165 | @inproceedings{pascual19_interspeech,
title = {{Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks}},
author = {Santiago Pascual and Mirco Ravanelli and Joan Serrà and Antonio Bonafonte and Yoshua Bengio},
year = {2019},
booktitle = {{Interspeech 2019}},
pages ... | Learning good representations without supervision is still an open
issue in machine learning, and is particularly challenging for speech
signals, which are often characterized by long sequences with a complex
hierarchical structure. Some recent works, however, have shown that
it is possible to derive useful speech repr... | 1904.03416 | title_snapshot |
nellore19_interspeech | Excitation Source and Vocal Tract System Based Acoustic Features for Detection of Nasals in Continuous Speech | [
"Bhanu Teja Nellore",
"Sri Harsha Dumpala",
"Karan Nathwani",
"Suryakanth V. Gangashetty"
] | https://www.isca-archive.org/interspeech_2019/nellore19_interspeech.html | https://www.isca-archive.org/interspeech_2019/nellore19_interspeech.pdf | 10.21437/Interspeech.2019-2785 | 166-170 | @inproceedings{nellore19_interspeech,
title = {{Excitation Source and Vocal Tract System Based Acoustic Features for Detection of Nasals in Continuous Speech}},
author = {Bhanu Teja Nellore and Sri Harsha Dumpala and Karan Nathwani and Suryakanth V. Gangashetty},
year = {2019},
booktitle = {{Intersp... | The aim of the current study is to propose acoustic features for detection
of nasals in continuous speech. Acoustic features that represent certain
characteristics of speech production are extracted. Features representing
excitation source characteristics are extracted using zero frequency
filtering method. Features re... | null | null |
chatziagapi19_interspeech | Data Augmentation Using GANs for Speech Emotion Recognition | [
"Aggelina Chatziagapi",
"Georgios Paraskevopoulos",
"Dimitris Sgouropoulos",
"Georgios Pantazopoulos",
"Malvina Nikandrou",
"Theodoros Giannakopoulos",
"Athanasios Katsamanis",
"Alexandros Potamianos",
"Shrikanth Narayanan"
] | https://www.isca-archive.org/interspeech_2019/chatziagapi19_interspeech.html | https://www.isca-archive.org/interspeech_2019/chatziagapi19_interspeech.pdf | 10.21437/Interspeech.2019-2561 | 171-175 | @inproceedings{chatziagapi19_interspeech,
title = {{Data Augmentation Using GANs for Speech Emotion Recognition}},
author = {Aggelina Chatziagapi and Georgios Paraskevopoulos and Dimitris Sgouropoulos and Georgios Pantazopoulos and Malvina Nikandrou and Theodoros Giannakopoulos and Athanasios Katsamanis and ... | In this work, we address the problem of data imbalance for the task
of Speech Emotion Recognition (SER). We investigate conditioned data
augmentation using Generative Adversarial Networks (GANs), in order
to generate samples for underrepresented emotions. We adapt and improve
a conditional GAN architecture to generate ... | null | null |
kons19_interspeech | High Quality, Lightweight and Adaptable TTS Using LPCNet | [
"Zvi Kons",
"Slava Shechtman",
"Alex Sorin",
"Carmel Rabinovitz",
"Ron Hoory"
] | https://www.isca-archive.org/interspeech_2019/kons19_interspeech.html | https://www.isca-archive.org/interspeech_2019/kons19_interspeech.pdf | 10.21437/Interspeech.2019-1705 | 176-180 | @inproceedings{kons19_interspeech,
title = {{High Quality, Lightweight and Adaptable TTS Using LPCNet}},
author = {Zvi Kons and Slava Shechtman and Alex Sorin and Carmel Rabinovitz and Ron Hoory},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {176--180},
doi = {10.21437/Inte... | We present a lightweight adaptable neural TTS system with high quality
output. The system is composed of three separate neural network blocks:
prosody prediction, acoustic feature prediction and Linear Prediction
Coding Net as a neural vocoder. This system can synthesize speech with
close to natural quality while runni... | 1905.00590 | title_snapshot |
lorenzotrueba19_interspeech | Towards Achieving Robust Universal Neural Vocoding | [
"Jaime Lorenzo-Trueba",
"Thomas Drugman",
"Javier Latorre",
"Thomas Merritt",
"Bartosz Putrycz",
"Roberto Barra-Chicote",
"Alexis Moinet",
"Vatsal Aggarwal"
] | https://www.isca-archive.org/interspeech_2019/lorenzotrueba19_interspeech.html | https://www.isca-archive.org/interspeech_2019/lorenzotrueba19_interspeech.pdf | 10.21437/Interspeech.2019-1424 | 181-185 | @inproceedings{lorenzotrueba19_interspeech,
title = {{Towards Achieving Robust Universal Neural Vocoding}},
author = {Jaime Lorenzo-Trueba and Thomas Drugman and Javier Latorre and Thomas Merritt and Bartosz Putrycz and Roberto Barra-Chicote and Alexis Moinet and Vatsal Aggarwal},
year = {2019},
boo... | This paper explores the potential universality of neural vocoders.
We train a WaveRNN-based vocoder on 74 speakers coming from 17 languages.
This vocoder is shown to be capable of generating speech of consistently
good quality (98% relative mean MUSHRA when compared to natural speech)
regardless of whether the input sp... | 1811.06292 | title_snapshot |
neekhara19_interspeech | Expediting TTS Synthesis with Adversarial Vocoding | [
"Paarth Neekhara",
"Chris Donahue",
"Miller Puckette",
"Shlomo Dubnov",
"Julian McAuley"
] | https://www.isca-archive.org/interspeech_2019/neekhara19_interspeech.html | https://www.isca-archive.org/interspeech_2019/neekhara19_interspeech.pdf | 10.21437/Interspeech.2019-3099 | 186-190 | @inproceedings{neekhara19_interspeech,
title = {{Expediting TTS Synthesis with Adversarial Vocoding}},
author = {Paarth Neekhara and Chris Donahue and Miller Puckette and Shlomo Dubnov and Julian McAuley},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {186--190},
doi = {10.2... | Recent approaches in text-to-speech (TTS) synthesis employ neural network
strategies to vocode perceptually-informed spectrogram representations
directly into listenable waveforms. Such vocoding procedures create
a computational bottleneck in modern TTS pipelines. We propose an alternative
approach which utilizes gener... | 1904.07944 | title_snapshot |
mustafa19_interspeech | Analysis by Adversarial Synthesis — A Novel Approach for Speech Vocoding | [
"Ahmed Mustafa",
"Arijit Biswas",
"Christian Bergler",
"Julia Schottenhamml",
"Andreas Maier"
] | https://www.isca-archive.org/interspeech_2019/mustafa19_interspeech.html | https://www.isca-archive.org/interspeech_2019/mustafa19_interspeech.pdf | 10.21437/Interspeech.2019-1195 | 191-195 | @inproceedings{mustafa19_interspeech,
title = {{Analysis by Adversarial Synthesis — A Novel Approach for Speech Vocoding}},
author = {Ahmed Mustafa and Arijit Biswas and Christian Bergler and Julia Schottenhamml and Andreas Maier},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {191-... | Classical parametric speech coding techniques provide a compact representation
for speech signals. This affords a very low transmission rate but with
a reduced perceptual quality of the reconstructed signals. Recently,
autoregressive deep generative models such as WaveNet and SampleRNN
have been used as speech vocoders... | 1907.00772 | title_snapshot |
wu19b_interspeech | Quasi-Periodic WaveNet Vocoder: A Pitch Dependent Dilated Convolution Model for Parametric Speech Generation | [
"Yi-Chiao Wu",
"Tomoki Hayashi",
"Patrick Lumban Tobing",
"Kazuhiro Kobayashi",
"Tomoki Toda"
] | https://www.isca-archive.org/interspeech_2019/wu19b_interspeech.html | https://www.isca-archive.org/interspeech_2019/wu19b_interspeech.pdf | 10.21437/Interspeech.2019-1232 | 196-200 | @inproceedings{wu19b_interspeech,
title = {{Quasi-Periodic WaveNet Vocoder: A Pitch Dependent Dilated Convolution Model for Parametric Speech Generation}},
author = {Yi-Chiao Wu and Tomoki Hayashi and Patrick Lumban Tobing and Kazuhiro Kobayashi and Tomoki Toda},
year = {2019},
booktitle = {{Intersp... | In this paper, we propose a quasi-periodic neural network (QPNet) vocoder
with a novel network architecture named pitch-dependent dilated convolution
(PDCNN) to improve the pitch controllability of WaveNet (WN) vocoder.
The effectiveness of the WN vocoder to generate high-fidelity speech
samples from given acoustic fea... | 1907.00797 | title_snapshot |
tian19_interspeech | A Speaker-Dependent WaveNet for Voice Conversion with Non-Parallel Data | [
"Xiaohai Tian",
"Eng Siong Chng",
"Haizhou Li"
] | https://www.isca-archive.org/interspeech_2019/tian19_interspeech.html | https://www.isca-archive.org/interspeech_2019/tian19_interspeech.pdf | 10.21437/Interspeech.2019-1514 | 201-205 | @inproceedings{tian19_interspeech,
title = {{A Speaker-Dependent WaveNet for Voice Conversion with Non-Parallel Data}},
author = {Xiaohai Tian and Eng Siong Chng and Haizhou Li},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {201--205},
doi = {10.21437/Interspeech.2019-1514}... | In a typical voice conversion system, vocoder is commonly used for
speech-to-features analysis and features-to-speech synthesis. However,
vocoder can be a source of speech quality degradation. This paper presents
a novel approach to voice conversion using WaveNet for non-parallel
training data. Instead of reconstructin... | 1902.03705 | title_judge |
zhao19_interspeech | Attention-Enhanced Connectionist Temporal Classification for Discrete Speech Emotion Recognition | [
"Ziping Zhao",
"Zhongtian Bao",
"Zixing Zhang",
"Nicholas Cummins",
"Haishuai Wang",
"Björn W. Schuller"
] | https://www.isca-archive.org/interspeech_2019/zhao19_interspeech.html | https://www.isca-archive.org/interspeech_2019/zhao19_interspeech.pdf | 10.21437/Interspeech.2019-1649 | 206-210 | @inproceedings{zhao19_interspeech,
title = {{Attention-Enhanced Connectionist Temporal Classification for Discrete Speech Emotion Recognition}},
author = {Ziping Zhao and Zhongtian Bao and Zixing Zhang and Nicholas Cummins and Haishuai Wang and Björn W. Schuller},
year = {2019},
booktitle = {{Inter... | Discrete speech emotion recognition (SER), the assignment of a single
emotion label to an entire speech utterance, is typically performed
as a sequence-to-label task. This approach, however, is limited, in
that it can result in models that do not capture temporal changes in
the speech signal, including those indicativ... | null | null |
li19b_interspeech | Attentive to Individual: A Multimodal Emotion Recognition Network with Personalized Attention Profile | [
"Jeng-Lin Li",
"Chi-Chun Lee"
] | https://www.isca-archive.org/interspeech_2019/li19b_interspeech.html | https://www.isca-archive.org/interspeech_2019/li19b_interspeech.pdf | 10.21437/Interspeech.2019-2044 | 211-215 | @inproceedings{li19b_interspeech,
title = {{Attentive to Individual: A Multimodal Emotion Recognition Network with Personalized Attention Profile}},
author = {Jeng-Lin Li and Chi-Chun Lee},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {211--215},
doi = {10.21437/Interspeech... | A growing number of human-centered applications benefit from continuous
advancements in the emotion recognition technology. Many emotion recognition
algorithms have been designed to model multimodal behavior cues to
achieve high performances. However, most of them do not consider the
modulating factors of an individual... | null | null |
gallardoantolin19_interspeech | A Saliency-Based Attention LSTM Model for Cognitive Load Classification from Speech | [
"Ascensión Gallardo-AntolÃn",
"Juan Manuel Montero"
] | https://www.isca-archive.org/interspeech_2019/gallardoantolin19_interspeech.html | https://www.isca-archive.org/interspeech_2019/gallardoantolin19_interspeech.pdf | 10.21437/Interspeech.2019-1603 | 216-220 | @inproceedings{gallardoantolin19_interspeech,
title = {{A Saliency-Based Attention LSTM Model for Cognitive Load Classification from Speech}},
author = {Ascensión Gallardo-AntolÃn and Juan Manuel Montero},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {216--220},
doi = {10... | Cognitive Load (CL) refers to the amount of mental demand that a given
task imposes on an individual’s cognitive system and it can affect
his/her productivity in very high load situations. In this paper, we
propose an automatic system capable of classifying the CL level of
a speaker by analyzing his/her voice. Our rese... | null | null |
mallolragolta19_interspeech | A Hierarchical Attention Network-Based Approach for Depression Detection from Transcribed Clinical Interviews | [
"Adria Mallol-Ragolta",
"Ziping Zhao",
"Lukas Stappen",
"Nicholas Cummins",
"Björn W. Schuller"
] | https://www.isca-archive.org/interspeech_2019/mallolragolta19_interspeech.html | https://www.isca-archive.org/interspeech_2019/mallolragolta19_interspeech.pdf | 10.21437/Interspeech.2019-2036 | 221-225 | @inproceedings{mallolragolta19_interspeech,
title = {{A Hierarchical Attention Network-Based Approach for Depression Detection from Transcribed Clinical Interviews}},
author = {Adria Mallol-Ragolta and Ziping Zhao and Lukas Stappen and Nicholas Cummins and Björn W. Schuller},
year = {2019},
booktit... | The high prevalence of depression in society has given rise to a need
for new digital tools that can aid its early detection. Among other
effects, depression impacts the use of language. Seeking to exploit
this, this work focuses on the detection of depressed and non-depressed
individuals through the analysis of lingui... | null | null |
carmantini19_interspeech | Untranscribed Web Audio for Low Resource Speech Recognition | [
"Andrea Carmantini",
"Peter Bell",
"Steve Renals"
] | https://www.isca-archive.org/interspeech_2019/carmantini19_interspeech.html | https://www.isca-archive.org/interspeech_2019/carmantini19_interspeech.pdf | 10.21437/Interspeech.2019-2623 | 226-230 | @inproceedings{carmantini19_interspeech,
title = {{Untranscribed Web Audio for Low Resource Speech Recognition}},
author = {Andrea Carmantini and Peter Bell and Steve Renals},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {226--230},
doi = {10.21437/Interspeech.2019-2623},
... | Speech recognition models are highly susceptible to mismatch in the
acoustic and language domains between the training and the evaluation
data. For low resource languages, it is difficult to obtain transcribed
speech for target domains, while untranscribed data can be collected
with minimal effort. Recently, a method a... | null | null |
luscher19_interspeech | RWTH ASR Systems for LibriSpeech: Hybrid vs Attention | [
"Christoph Lüscher",
"Eugen Beck",
"Kazuki Irie",
"Markus Kitza",
"Wilfried Michel",
"Albert Zeyer",
"Ralf Schlüter",
"Hermann Ney"
] | https://www.isca-archive.org/interspeech_2019/luscher19_interspeech.html | https://www.isca-archive.org/interspeech_2019/luscher19_interspeech.pdf | 10.21437/Interspeech.2019-1780 | 231-235 | @inproceedings{luscher19_interspeech,
title = {{RWTH ASR Systems for LibriSpeech: Hybrid vs Attention}},
author = {Christoph Lüscher and Eugen Beck and Kazuki Irie and Markus Kitza and Wilfried Michel and Albert Zeyer and Ralf Schlüter and Hermann Ney},
year = {2019},
booktitle = {{Interspeech 201... | We present state-of-the-art automatic speech recognition (ASR) systems
employing a standard hybrid DNN/HMM architecture compared to an attention-based
encoder-decoder design for the LibriSpeech task. Detailed descriptions
of the system development, including model design, pretraining schemes,
training schedules, and op... | 1905.03072 | title_judge |
kanda19_interspeech | Auxiliary Interference Speaker Loss for Target-Speaker Speech Recognition | [
"Naoyuki Kanda",
"Shota Horiguchi",
"Ryoichi Takashima",
"Yusuke Fujita",
"Kenji Nagamatsu",
"Shinji Watanabe"
] | https://www.isca-archive.org/interspeech_2019/kanda19_interspeech.html | https://www.isca-archive.org/interspeech_2019/kanda19_interspeech.pdf | 10.21437/Interspeech.2019-1126 | 236-240 | @inproceedings{kanda19_interspeech,
title = {{Auxiliary Interference Speaker Loss for Target-Speaker Speech Recognition}},
author = {Naoyuki Kanda and Shota Horiguchi and Ryoichi Takashima and Yusuke Fujita and Kenji Nagamatsu and Shinji Watanabe},
year = {2019},
booktitle = {{Interspeech 2019}},
... | In this paper, we propose a novel auxiliary loss function for target-speaker
automatic speech recognition (ASR). Our method automatically extracts
and transcribes target speaker’s utterances from a monaural mixture
of multiple speakers speech given a short sample of the target speaker.
The proposed auxiliary loss funct... | 1906.10876 | title_snapshot |
meng19_interspeech | Speaker Adaptation for Attention-Based End-to-End Speech Recognition | [
"Zhong Meng",
"Yashesh Gaur",
"Jinyu Li",
"Yifan Gong"
] | https://www.isca-archive.org/interspeech_2019/meng19_interspeech.html | https://www.isca-archive.org/interspeech_2019/meng19_interspeech.pdf | 10.21437/Interspeech.2019-3135 | 241-245 | @inproceedings{meng19_interspeech,
title = {{Speaker Adaptation for Attention-Based End-to-End Speech Recognition}},
author = {Zhong Meng and Yashesh Gaur and Jinyu Li and Yifan Gong},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {241--245},
doi = {10.21437/Interspeech.2019... | We propose three regularization-based speaker adaptation approaches
to adapt the attention-based encoder-decoder (AED) model with very
limited adaptation data from target speakers for end-to-end automatic
speech recognition. The first method is Kullback-Leibler divergence
(KLD) regularization, in which the output distr... | 1911.03762 | title_snapshot |
wang19_interspeech | Large Margin Training for Attention Based End-to-End Speech Recognition | [
"Peidong Wang",
"Jia Cui",
"Chao Weng",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2019/wang19_interspeech.html | https://www.isca-archive.org/interspeech_2019/wang19_interspeech.pdf | 10.21437/Interspeech.2019-1680 | 246-250 | @inproceedings{wang19_interspeech,
title = {{Large Margin Training for Attention Based End-to-End Speech Recognition}},
author = {Peidong Wang and Jia Cui and Chao Weng and Dong Yu},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {246--250},
doi = {10.21437/Interspeech.2019-1... | End-to-end speech recognition systems are typically evaluated using
the maximum a posterior criterion. Since only one hypothesis is involved
during evaluation, the ideal number of hypotheses for training should
also be one. In this study, we propose a large margin training scheme
for attention based end-to-end speech r... | null | null |
mac19_interspeech | Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition | [
"Khoi-Nguyen C. Mac",
"Xiaodong Cui",
"Wei Zhang",
"Michael Picheny"
] | https://www.isca-archive.org/interspeech_2019/mac19_interspeech.html | https://www.isca-archive.org/interspeech_2019/mac19_interspeech.pdf | 10.21437/Interspeech.2019-2641 | 251-255 | @inproceedings{mac19_interspeech,
title = {{Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition}},
author = {Khoi-Nguyen C. Mac and Xiaodong Cui and Wei Zhang and Michael Picheny},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {251--255... | In automatic speech recognition (ASR), wideband (WB) and narrowband
(NB) speech signals with different sampling rates typically use separate
acoustic models. Therefore mixed-bandwidth (MB) acoustic modeling has
important practical values for ASR system deployment. In this paper,
we extensively investigate large-scale M... | 1907.04887 | title_snapshot |
milde19_interspeech | SparseSpeech: Unsupervised Acoustic Unit Discovery with Memory-Augmented Sequence Autoencoders | [
"Benjamin Milde",
"Chris Biemann"
] | https://www.isca-archive.org/interspeech_2019/milde19_interspeech.html | https://www.isca-archive.org/interspeech_2019/milde19_interspeech.pdf | 10.21437/Interspeech.2019-2938 | 256-260 | @inproceedings{milde19_interspeech,
title = {{SparseSpeech: Unsupervised Acoustic Unit Discovery with Memory-Augmented Sequence Autoencoders}},
author = {Benjamin Milde and Chris Biemann},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {256--260},
doi = {10.21437/Interspeech.... | We propose a sparse sequence autoencoder model for unsupervised acoustic
unit discovery, based on bidirectional LSTM encoders/decoders with
a sparsity-inducing bottleneck. The sparsity layer is based on memory-augmented
neural networks, with a differentiable embedding memory bank addressed
from the encoder. The decoder... | null | null |
ondel19_interspeech | Bayesian Subspace Hidden Markov Model for Acoustic Unit Discovery | [
"Lucas Ondel",
"Hari Krishna Vydana",
"Lukáš Burget",
"Jan Äernocký"
] | https://www.isca-archive.org/interspeech_2019/ondel19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ondel19_interspeech.pdf | 10.21437/Interspeech.2019-2224 | 261-265 | @inproceedings{ondel19_interspeech,
title = {{Bayesian Subspace Hidden Markov Model for Acoustic Unit Discovery}},
author = {Lucas Ondel and Hari Krishna Vydana and Lukáš Burget and Jan Äernocký},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {261--265},
doi = {10.21437/... | This work tackles the problem of learning a set of language specific
acoustic units from unlabeled speech recordings given a set of labeled
recordings from other languages. Our approach may be described by the
following two steps procedure: first the model learns the notion of
acoustic units from the labelled data and ... | 1904.03876 | title_snapshot |
higuchi19_interspeech | Speaker Adversarial Training of DPGMM-Based Feature Extractor for Zero-Resource Languages | [
"Yosuke Higuchi",
"Naohiro Tawara",
"Tetsunori Kobayashi",
"Tetsuji Ogawa"
] | https://www.isca-archive.org/interspeech_2019/higuchi19_interspeech.html | https://www.isca-archive.org/interspeech_2019/higuchi19_interspeech.pdf | 10.21437/Interspeech.2019-2052 | 266-270 | @inproceedings{higuchi19_interspeech,
title = {{Speaker Adversarial Training of DPGMM-Based Feature Extractor for Zero-Resource Languages}},
author = {Yosuke Higuchi and Naohiro Tawara and Tetsunori Kobayashi and Tetsuji Ogawa},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {266--27... | We propose a novel framework for extracting speaker-invariant features
for zero-resource languages. A deep neural network (DNN)-based acoustic
model is normalized against speakers via adversarial training: a multi-task
learning process trains a shared bottleneck feature to be discriminative
to phonemes and independent ... | null | null |
prasad19_interspeech | Building Large-Vocabulary ASR Systems for Languages Without Any Audio Training Data | [
"Manasa Prasad",
"Daan van Esch",
"Sandy Ritchie",
"Jonas Fromseier Mortensen"
] | https://www.isca-archive.org/interspeech_2019/prasad19_interspeech.html | https://www.isca-archive.org/interspeech_2019/prasad19_interspeech.pdf | 10.21437/Interspeech.2019-1775 | 271-275 | @inproceedings{prasad19_interspeech,
title = {{Building Large-Vocabulary ASR Systems for Languages Without Any Audio Training Data}},
author = {Manasa Prasad and Daan van Esch and Sandy Ritchie and Jonas Fromseier Mortensen},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {271--275},... | When building automatic speech recognition (ASR) systems, typically
some amount of audio and text data in the target language is needed.
While text data can be obtained relatively easily across many languages,
transcribed audio data is challenging to obtain. This presents a barrier
to making voice technologies availabl... | null | null |
azuh19_interspeech | Towards Bilingual Lexicon Discovery From Visually Grounded Speech Audio | [
"Emmanuel Azuh",
"David Harwath",
"James Glass"
] | https://www.isca-archive.org/interspeech_2019/azuh19_interspeech.html | https://www.isca-archive.org/interspeech_2019/azuh19_interspeech.pdf | 10.21437/Interspeech.2019-1718 | 276-280 | @inproceedings{azuh19_interspeech,
title = {{Towards Bilingual Lexicon Discovery From Visually Grounded Speech Audio}},
author = {Emmanuel Azuh and David Harwath and James Glass},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {276--280},
doi = {10.21437/Interspeech.2019-1718... | In this paper, we present a method for the discovery of word-like units
and their approximate translations from visually grounded speech across
multiple languages. We first train a neural network model to map images
and their spoken audio captions in both English and Hindi to a shared,
multimodal embedding space. Next,... | null | null |
feng19_interspeech | Improving Unsupervised Subword Modeling via Disentangled Speech Representation Learning and Transformation | [
"Siyuan Feng",
"Tan Lee"
] | https://www.isca-archive.org/interspeech_2019/feng19_interspeech.html | https://www.isca-archive.org/interspeech_2019/feng19_interspeech.pdf | 10.21437/Interspeech.2019-1338 | 281-285 | @inproceedings{feng19_interspeech,
title = {{Improving Unsupervised Subword Modeling via Disentangled Speech Representation Learning and Transformation}},
author = {Siyuan Feng and Tan Lee},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {281--285},
doi = {10.21437/Interspeec... | This study tackles unsupervised subword modeling in the zero-resource
scenario, learning frame-level speech representation that is phonetically
discriminative and speaker-invariant, using only untranscribed speech
for target languages. Frame label acquisition is an essential step
in solving this problem. High quality f... | 1906.07245 | title_snapshot |
nissen19_interspeech | Listeners’ Ability to Identify the Gender of Preadolescent Children in Different Linguistic Contexts | [
"Shawn Nissen",
"Sharalee Blunck",
"Anita Dromey",
"Christopher Dromey"
] | https://www.isca-archive.org/interspeech_2019/nissen19_interspeech.html | https://www.isca-archive.org/interspeech_2019/nissen19_interspeech.pdf | 10.21437/Interspeech.2019-1865 | 286-290 | @inproceedings{nissen19_interspeech,
title = {{Listeners’ Ability to Identify the Gender of Preadolescent Children in Different Linguistic Contexts}},
author = {Shawn Nissen and Sharalee Blunck and Anita Dromey and Christopher Dromey},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {... | This study evaluated listeners’ ability to identify the gender
of preadolescent children from speech samples of varying length and
linguistic context. The listeners were presented with a total of 190
speech samples in four different categories of linguistic context:
segments, words, sentences, and discourse. The listen... | null | null |
ahlers19_interspeech | Sibilant Variation in New Englishes: A Comparative Sociophonetic Study of Trinidadian and American English /s(tr)/-Retraction | [
"Wiebke Ahlers",
"Philipp Meer"
] | https://www.isca-archive.org/interspeech_2019/ahlers19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ahlers19_interspeech.pdf | 10.21437/Interspeech.2019-1821 | 291-295 | @inproceedings{ahlers19_interspeech,
title = {{Sibilant Variation in New Englishes: A Comparative Sociophonetic Study of Trinidadian and American English /s(tr)/-Retraction}},
author = {Wiebke Ahlers and Philipp Meer},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {291--295},
doi ... | The retraction of /s/, particularly in /str/ clusters, toward [ʃ]
has been investigated in British, Australian, and American English
and shown to be conditioned phonetically and sociolinguistically. To
date, however, no research exists on the retraction of /s/ in New Englishes,
the nativized Englishes spoken in postcol... | null | null |
gubian19_interspeech | Tracking the New Zealand English NEAR/SQUARE Merger Using Functional Principal Components Analysis | [
"Michele Gubian",
"Jonathan Harrington",
"Mary Stevens",
"Florian Schiel",
"Paul Warren"
] | https://www.isca-archive.org/interspeech_2019/gubian19_interspeech.html | https://www.isca-archive.org/interspeech_2019/gubian19_interspeech.pdf | 10.21437/Interspeech.2019-2115 | 296-300 | @inproceedings{gubian19_interspeech,
title = {{Tracking the New Zealand English NEAR/SQUARE Merger Using Functional Principal Components Analysis}},
author = {Michele Gubian and Jonathan Harrington and Mary Stevens and Florian Schiel and Paul Warren},
year = {2019},
booktitle = {{Interspeech 2019}},... | The focus of the study is the application of functional principal components
analysis (FPCA) to a sound change in progress in which the square
and near falling diphthongs are merging in New Zealand English. FPCA
approximated the trajectory shapes of the first two formant frequencies
(F1/F2) in a large acoustic databa... | null | null |
gessinger19_interspeech | Phonetic Accommodation in a Wizard-of-Oz Experiment: Intonation and Segments | [
"Iona Gessinger",
"Bernd Möbius",
"Bistra Andreeva",
"Eran Raveh",
"Ingmar Steiner"
] | https://www.isca-archive.org/interspeech_2019/gessinger19_interspeech.html | https://www.isca-archive.org/interspeech_2019/gessinger19_interspeech.pdf | 10.21437/Interspeech.2019-2445 | 301-305 | @inproceedings{gessinger19_interspeech,
title = {{Phonetic Accommodation in a Wizard-of-Oz Experiment: Intonation and Segments}},
author = {Iona Gessinger and Bernd Möbius and Bistra Andreeva and Eran Raveh and Ingmar Steiner},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {301--30... | This paper discusses phonetic accommodation of 20 native German speakers
interacting with the simulated spoken dialogue system Mirabella in
a Wizard-of-Oz experiment. The study examines intonation of wh-questions
and pronunciation of allophonic contrasts in German. In a question-and-answer
exchange with the system, the... | null | null |
niebuhr19b_interspeech | PASCAL and DPA: A Pilot Study on Using Prosodic Competence Scores to Predict Communicative Skills for Team Working and Public Speaking | [
"Oliver Niebuhr",
"Jan Michalsky"
] | https://www.isca-archive.org/interspeech_2019/niebuhr19b_interspeech.html | https://www.isca-archive.org/interspeech_2019/niebuhr19b_interspeech.pdf | 10.21437/Interspeech.2019-3034 | 306-310 | @inproceedings{niebuhr19b_interspeech,
title = {{PASCAL and DPA: A Pilot Study on Using Prosodic Competence Scores to Predict Communicative Skills for Team Working and Public Speaking}},
author = {Oliver Niebuhr and Jan Michalsky},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {306-... | Strong communication skills in public-speaking and team-working exercises
are associated with specific acoustic-prosodic profiles and strategies.
We hypothesize that analyzing and assessing these profiles and strategies
allows us to predict communicative skills. To that end, we used two
analysis methods, one for charis... | null | null |
michalsky19_interspeech | Towards the Prosody of Persuasion in Competitive Negotiation. The Relationship Between f0 and Negotiation Success in Same Sex Sales Tasks | [
"Jan Michalsky",
"Heike Schoormann",
"Thomas Schultze"
] | https://www.isca-archive.org/interspeech_2019/michalsky19_interspeech.html | https://www.isca-archive.org/interspeech_2019/michalsky19_interspeech.pdf | 10.21437/Interspeech.2019-3031 | 311-315 | @inproceedings{michalsky19_interspeech,
title = {{Towards the Prosody of Persuasion in Competitive Negotiation. The Relationship Between f0 and Negotiation Success in Same Sex Sales Tasks}},
author = {Jan Michalsky and Heike Schoormann and Thomas Schultze},
year = {2019},
booktitle = {{Interspeech 2... | Prosodic features play a key role in a speaker’s persuasive power.
However, previous studies on persuasion have been focused on public
speaking and the signaling of leadership, while acoustic studies on
negotiation have been primarily concerned with cooperative interactions.
In this study we are taking a first step int... | null | null |
sager19_interspeech | VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English | [
"Jacob Sager",
"Ravi Shankar",
"Jacob Reinhold",
"Archana Venkataraman"
] | https://www.isca-archive.org/interspeech_2019/sager19_interspeech.html | https://www.isca-archive.org/interspeech_2019/sager19_interspeech.pdf | 10.21437/Interspeech.2019-1413 | 316-320 | @inproceedings{sager19_interspeech,
title = {{VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English}},
author = {Jacob Sager and Ravi Shankar and Jacob Reinhold and Archana Venkataraman},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {316--32... | We introduce the Varied Emotion in Syntactically Uniform Speech (VESUS)
repository as a new resource for the speech community. VESUS is a lexically
controlled database, in which a semantically neutral script is portrayed
with different emotional inflections. In total, VESUS contains over
250 distinct phrases, each read... | null | null |
koh19_interspeech | Building the Singapore English National Speech Corpus | [
"Jia Xin Koh",
"Aqilah Mislan",
"Kevin Khoo",
"Brian Ang",
"Wilson Ang",
"Charmaine Ng",
"Ying-Ying Tan"
] | https://www.isca-archive.org/interspeech_2019/koh19_interspeech.html | https://www.isca-archive.org/interspeech_2019/koh19_interspeech.pdf | 10.21437/Interspeech.2019-1525 | 321-325 | @inproceedings{koh19_interspeech,
title = {{Building the Singapore English National Speech Corpus}},
author = {Jia Xin Koh and Aqilah Mislan and Kevin Khoo and Brian Ang and Wilson Ang and Charmaine Ng and Ying-Ying Tan},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {321--325},
d... | The National Speech Corpus (NSC) is the first large-scale Singapore
English corpus spearheaded by the Info-communications and Media Development
Authority of Singapore. It aims to become an important source of open
speech data for automatic speech recognition (ASR) research and speech-related
applications. The first rel... | null | null |
picheny19_interspeech | Challenging the Boundaries of Speech Recognition: The MALACH Corpus | [
"Michael Picheny",
"Zoltán Tüske",
"Brian Kingsbury",
"Kartik Audhkhasi",
"Xiaodong Cui",
"George Saon"
] | https://www.isca-archive.org/interspeech_2019/picheny19_interspeech.html | https://www.isca-archive.org/interspeech_2019/picheny19_interspeech.pdf | 10.21437/Interspeech.2019-1907 | 326-330 | @inproceedings{picheny19_interspeech,
title = {{Challenging the Boundaries of Speech Recognition: The MALACH Corpus}},
author = {Michael Picheny and Zoltán Tüske and Brian Kingsbury and Kartik Audhkhasi and Xiaodong Cui and George Saon},
year = {2019},
booktitle = {{Interspeech 2019}},
pages ... | There has been huge progress in speech recognition over the last several
years. Tasks once thought extremely difficult, such as SWITCHBOARD,
now approach levels of human performance. The MALACH corpus (LDC catalog
LDC2012S05), a 375-Hour subset of a large archive of Holocaust testimonies
collected by the Survivors of t... | 1908.03455 | title_snapshot |
ramteke19_interspeech | NITK Kids’ Speech Corpus | [
"Pravin Bhaskar Ramteke",
"Sujata Supanekar",
"Pradyoth Hegde",
"Hanna Nelson",
"Venkataraja Aithal",
"Shashidhar G. Koolagudi"
] | https://www.isca-archive.org/interspeech_2019/ramteke19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ramteke19_interspeech.pdf | 10.21437/Interspeech.2019-2061 | 331-335 | @inproceedings{ramteke19_interspeech,
title = {{NITK Kids’ Speech Corpus}},
author = {Pravin Bhaskar Ramteke and Sujata Supanekar and Pradyoth Hegde and Hanna Nelson and Venkataraja Aithal and Shashidhar G. Koolagudi},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {331--335},
doi ... | This paper introduces speech database for analyzing children’s
speech. The proposed database of children is recorded in Kannada language
(one of the South Indian languages) from children between age 2.5 to
6.5 years. The database is named as National Institute of Technology
Karnataka Kids’ Speech Corpus (NITK Kids’ Spe... | null | null |
ali19_interspeech | Towards Variability Resistant Dialectal Speech Evaluation | [
"Ahmed Ali",
"Salam Khalifa",
"Nizar Habash"
] | https://www.isca-archive.org/interspeech_2019/ali19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ali19_interspeech.pdf | 10.21437/Interspeech.2019-2692 | 336-340 | @inproceedings{ali19_interspeech,
title = {{Towards Variability Resistant Dialectal Speech Evaluation}},
author = {Ahmed Ali and Salam Khalifa and Nizar Habash},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {336--340},
doi = {10.21437/Interspeech.2019-2692},
issn = {... | We study the problem of evaluating automatic speech recognition (ASR)
systems that target dialectal speech input. A major challenge in this
case is that the orthography of dialects is typically not standardized.
From an ASR evaluation perspective, this means that there is no clear
gold standard for the expected output,... | null | null |
fallgren19_interspeech | How to Annotate 100 Hours in 45 Minutes | [
"Per Fallgren",
"Zofia Malisz",
"Jens Edlund"
] | https://www.isca-archive.org/interspeech_2019/fallgren19_interspeech.html | https://www.isca-archive.org/interspeech_2019/fallgren19_interspeech.pdf | 10.21437/Interspeech.2019-1648 | 341-345 | @inproceedings{fallgren19_interspeech,
title = {{How to Annotate 100 Hours in 45 Minutes}},
author = {Per Fallgren and Zofia Malisz and Jens Edlund},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {341--345},
doi = {10.21437/Interspeech.2019-1648},
issn = {2958-1796},
... | Speech data found in the wild hold many advantages over artificially
constructed speech corpora in terms of ecological validity and cultural
worth. Perhaps most importantly, there is a lot of it. However, the
combination of great quantity, noisiness and variation poses a challenge
for its access and processing. General... | null | null |
diez19_interspeech | Bayesian HMM Based x-Vector Clustering for Speaker Diarization | [
"Mireia Diez",
"Lukáš Burget",
"Shuai Wang",
"Johan Rohdin",
"Jan Äernocký"
] | https://www.isca-archive.org/interspeech_2019/diez19_interspeech.html | https://www.isca-archive.org/interspeech_2019/diez19_interspeech.pdf | 10.21437/Interspeech.2019-2813 | 346-350 | @inproceedings{diez19_interspeech,
title = {{Bayesian HMM Based x-Vector Clustering for Speaker Diarization}},
author = {Mireia Diez and Lukáš Burget and Shuai Wang and Johan Rohdin and Jan Äernocký},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {346--350},
doi = {10.21... | This paper presents a simplified version of the previously proposed
diarization algorithm based on Bayesian Hidden Markov Models, which
uses Variational Bayesian inference for very fast and robust clustering
of x-vector (neural network based speaker embeddings). The presented
results show that this clustering algorithm... | null | null |
vestman19_interspeech | Unleashing the Unused Potential of i-Vectors Enabled by GPU Acceleration | [
"Ville Vestman",
"Kong Aik Lee",
"Tomi H. Kinnunen",
"Takafumi Koshinaka"
] | https://www.isca-archive.org/interspeech_2019/vestman19_interspeech.html | https://www.isca-archive.org/interspeech_2019/vestman19_interspeech.pdf | 10.21437/Interspeech.2019-1955 | 351-355 | @inproceedings{vestman19_interspeech,
title = {{Unleashing the Unused Potential of i-Vectors Enabled by GPU Acceleration}},
author = {Ville Vestman and Kong Aik Lee and Tomi H. Kinnunen and Takafumi Koshinaka},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {351--355},
doi = ... | Speaker embeddings are continuous-value vector representations that
allow easy comparison between voices of speakers with simple geometric
operations. Among others, i-vector and x-vector have emerged as the
mainstream methods for speaker embedding. In this paper, we illustrate
the use of modern computation platform to ... | 1906.08556 | title_snapshot |
shon19_interspeech | MCE 2018: The 1st Multi-Target Speaker Detection and Identification Challenge Evaluation | [
"Suwon Shon",
"Najim Dehak",
"Douglas Reynolds",
"James Glass"
] | https://www.isca-archive.org/interspeech_2019/shon19_interspeech.html | https://www.isca-archive.org/interspeech_2019/shon19_interspeech.pdf | 10.21437/Interspeech.2019-1572 | 356-360 | @inproceedings{shon19_interspeech,
title = {{MCE 2018: The 1st Multi-Target Speaker Detection and Identification Challenge Evaluation}},
author = {Suwon Shon and Najim Dehak and Douglas Reynolds and James Glass},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {356--360},
doi ... | The Multi-target Challenge aims to assess how well current speech technology
is able to determine whether or not a recorded utterance was spoken
by one of a large number of blacklisted speakers. It is a form of multi-target
speaker detection based on real-world telephone conversations. Data
recordings are generated fro... | 1904.04240 | title_snapshot |
gao19_interspeech | Improving Aggregation and Loss Function for Better Embedding Learning in End-to-End Speaker Verification System | [
"Zhifu Gao",
"Yan Song",
"Ian McLoughlin",
"Pengcheng Li",
"Yiheng Jiang",
"Li-Rong Dai"
] | https://www.isca-archive.org/interspeech_2019/gao19_interspeech.html | https://www.isca-archive.org/interspeech_2019/gao19_interspeech.pdf | 10.21437/Interspeech.2019-1489 | 361-365 | @inproceedings{gao19_interspeech,
title = {{Improving Aggregation and Loss Function for Better Embedding Learning in End-to-End Speaker Verification System}},
author = {Zhifu Gao and Yan Song and Ian McLoughlin and Pengcheng Li and Yiheng Jiang and Li-Rong Dai},
year = {2019},
booktitle = {{Interspe... | Deep embedding learning based speaker verification (SV) methods have
recently achieved significant performance improvement over traditional
i-vector systems, especially for short duration utterances. Embedding
learning commonly consists of three components: frame-level feature
processing, utterance-level embedding lear... | null | null |
lin19_interspeech | LSTM Based Similarity Measurement with Spectral Clustering for Speaker Diarization | [
"Qingjian Lin",
"Ruiqing Yin",
"Ming Li",
"Hervé Bredin",
"Claude Barras"
] | https://www.isca-archive.org/interspeech_2019/lin19_interspeech.html | https://www.isca-archive.org/interspeech_2019/lin19_interspeech.pdf | 10.21437/Interspeech.2019-1388 | 366-370 | @inproceedings{lin19_interspeech,
title = {{LSTM Based Similarity Measurement with Spectral Clustering for Speaker Diarization}},
author = {Qingjian Lin and Ruiqing Yin and Ming Li and Hervé Bredin and Claude Barras},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {366--370},
doi ... | More and more neural network approaches have achieved considerable
improvement upon submodules of speaker diarization system, including
speaker change detection and segment-wise speaker embedding extraction.
Still, in the clustering stage, traditional algorithms like probabilistic
linear discriminant analysis (PLDA) ar... | 1907.10393 | title_snapshot |
chung19b_interspeech | Who Said That?: Audio-Visual Speaker Diarisation of Real-World Meetings | [
"Joon Son Chung",
"Bong-Jin Lee",
"Icksang Han"
] | https://www.isca-archive.org/interspeech_2019/chung19b_interspeech.html | https://www.isca-archive.org/interspeech_2019/chung19b_interspeech.pdf | 10.21437/Interspeech.2019-3116 | 371-375 | @inproceedings{chung19b_interspeech,
title = {{Who Said That?: Audio-Visual Speaker Diarisation of Real-World Meetings}},
author = {Joon Son Chung and Bong-Jin Lee and Icksang Han},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {371--375},
doi = {10.21437/Interspeech.2019-31... | The goal of this work is to determine ‘who spoke when’
in real-world meetings. The method takes surround-view video and single
or multi-channel audio as inputs, and generates robust diarisation
outputs. To achieve this, we propose a novel iterative approach that first
enrolls speaker models using audio-visual correspon... | 1906.10042 | title_snapshot |
xie19_interspeech | Multi-PLDA Diarization on Children’s Speech | [
"Jiamin Xie",
"Leibny Paola GarcÃa-Perera",
"Daniel Povey",
"Sanjeev Khudanpur"
] | https://www.isca-archive.org/interspeech_2019/xie19_interspeech.html | https://www.isca-archive.org/interspeech_2019/xie19_interspeech.pdf | 10.21437/Interspeech.2019-2961 | 376-380 | @inproceedings{xie19_interspeech,
title = {{Multi-PLDA Diarization on Children’s Speech}},
author = {Jiamin Xie and Leibny Paola GarcÃa-Perera and Daniel Povey and Sanjeev Khudanpur},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {376--380},
doi = {10.21437/Interspeech.2019... | Children’s speech and other vocalizations pose challenges for
speaker diarization. The spontaneity of kids causes rapid or delayed
phonetic variations in an utterance, which makes speaker’s information
difficult to extract. Fast speaker turns and long overlap in conversations
between children and their guardians makes ... | null | null |
mccree19_interspeech | Speaker Diarization Using Leave-One-Out Gaussian PLDA Clustering of DNN Embeddings | [
"Alan McCree",
"Gregory Sell",
"Daniel Garcia-Romero"
] | https://www.isca-archive.org/interspeech_2019/mccree19_interspeech.html | https://www.isca-archive.org/interspeech_2019/mccree19_interspeech.pdf | 10.21437/Interspeech.2019-2912 | 381-385 | @inproceedings{mccree19_interspeech,
title = {{Speaker Diarization Using Leave-One-Out Gaussian PLDA Clustering of DNN Embeddings}},
author = {Alan McCree and Gregory Sell and Daniel Garcia-Romero},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {381--385},
doi = {10.21437/In... | Many modern systems for speaker diarization, such as the top-performing
JHU system in the DIHARD 2018 challenge, rely on clustering of DNN
speaker embeddings followed by HMM resegmentation. Two problems with
this approach are that parameters need significant retuning for different
applications, and that the DNN contrib... | null | null |
ghahabi19_interspeech | Speaker-Corrupted Embeddings for Online Speaker Diarization | [
"Omid Ghahabi",
"Volker Fischer"
] | https://www.isca-archive.org/interspeech_2019/ghahabi19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ghahabi19_interspeech.pdf | 10.21437/Interspeech.2019-2756 | 386-390 | @inproceedings{ghahabi19_interspeech,
title = {{Speaker-Corrupted Embeddings for Online Speaker Diarization}},
author = {Omid Ghahabi and Volker Fischer},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {386--390},
doi = {10.21437/Interspeech.2019-2756},
issn = {2958-17... | Speaker diarization is more challenging in presence of background noise
or music, frequent speaker changes, and cross talks. In an online scenario,
the decision should be made at time, given only the current short segment
and the speakers detected in the past, which makes the task even harder.
In this work, an online r... | null | null |
park19_interspeech | Speaker Diarization with Lexical Information | [
"Tae Jin Park",
"Kyu J. Han",
"Jing Huang",
"Xiaodong He",
"Bowen Zhou",
"Panayiotis Georgiou",
"Shrikanth Narayanan"
] | https://www.isca-archive.org/interspeech_2019/park19_interspeech.html | https://www.isca-archive.org/interspeech_2019/park19_interspeech.pdf | 10.21437/Interspeech.2019-1947 | 391-395 | @inproceedings{park19_interspeech,
title = {{Speaker Diarization with Lexical Information}},
author = {Tae Jin Park and Kyu J. Han and Jing Huang and Xiaodong He and Bowen Zhou and Panayiotis Georgiou and Shrikanth Narayanan},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {391--395}... | This work presents a novel approach for speaker diarization to leverage
lexical information provided by automatic speech recognition. We propose
a speaker diarization system that can incorporate word-level speaker
turn probabilities with speaker embeddings into a speaker clustering
process to improve the overall diariz... | 2004.06756 | title_snapshot |
shafey19_interspeech | Joint Speech Recognition and Speaker Diarization via Sequence Transduction | [
"Laurent El Shafey",
"Hagen Soltau",
"Izhak Shafran"
] | https://www.isca-archive.org/interspeech_2019/shafey19_interspeech.html | https://www.isca-archive.org/interspeech_2019/shafey19_interspeech.pdf | 10.21437/Interspeech.2019-1943 | 396-400 | @inproceedings{shafey19_interspeech,
title = {{Joint Speech Recognition and Speaker Diarization via Sequence Transduction}},
author = {Laurent El Shafey and Hagen Soltau and Izhak Shafran},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {396--400},
doi = {10.21437/Interspeech... | Speech applications dealing with conversations require not only recognizing
the spoken words, but also determining who spoke when. The task of
assigning words to speakers is typically addressed by merging the outputs
of two separate systems, namely, an automatic speech recognition (ASR)
system and a speaker diarization... | 1907.05337 | title_snapshot |
cumani19_interspeech | Normal Variance-Mean Mixtures for Unsupervised Score Calibration | [
"Sandro Cumani"
] | https://www.isca-archive.org/interspeech_2019/cumani19_interspeech.html | https://www.isca-archive.org/interspeech_2019/cumani19_interspeech.pdf | 10.21437/Interspeech.2019-1609 | 401-405 | @inproceedings{cumani19_interspeech,
title = {{Normal Variance-Mean Mixtures for Unsupervised Score Calibration}},
author = {Sandro Cumani},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {401--405},
doi = {10.21437/Interspeech.2019-1609},
issn = {2958-1796},
} | Generative calibration models have shown to be an effective alternative
to traditional discriminative score calibration techniques, such as
Logistic Regression (LogReg). Provided that the score distribution
assumptions are sufficiently accurate, generative approaches not only
have similar or better performance with res... | null | null |
yamamoto19_interspeech | Speaker Augmentation and Bandwidth Extension for Deep Speaker Embedding | [
"Hitoshi Yamamoto",
"Kong Aik Lee",
"Koji Okabe",
"Takafumi Koshinaka"
] | https://www.isca-archive.org/interspeech_2019/yamamoto19_interspeech.html | https://www.isca-archive.org/interspeech_2019/yamamoto19_interspeech.pdf | 10.21437/Interspeech.2019-1508 | 406-410 | @inproceedings{yamamoto19_interspeech,
title = {{Speaker Augmentation and Bandwidth Extension for Deep Speaker Embedding}},
author = {Hitoshi Yamamoto and Kong Aik Lee and Koji Okabe and Takafumi Koshinaka},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {406--410},
doi = {10... | This paper investigates a novel data augmentation approach to train
deep neural networks (DNNs) used for speaker embedding, i.e. to extract
representation that allows easy comparison between speaker voices with
a simple geometric operation. Data augmentation is used to create new
examples from an existing training set,... | null | null |
ylmaz19_interspeech | Large-Scale Speaker Diarization of Radio Broadcast Archives | [
"Emre Yılmaz",
"Adem Derinel",
"Kun Zhou",
"Henk van den Heuvel",
"Niko Brummer",
"Haizhou Li",
"David A. van Leeuwen"
] | https://www.isca-archive.org/interspeech_2019/ylmaz19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ylmaz19_interspeech.pdf | 10.21437/Interspeech.2019-1399 | 411-415 | @inproceedings{ylmaz19_interspeech,
title = {{Large-Scale Speaker Diarization of Radio Broadcast Archives}},
author = {Emre Yılmaz and Adem Derinel and Kun Zhou and Henk van den Heuvel and Niko Brummer and Haizhou Li and David A. van Leeuwen},
year = {2019},
booktitle = {{Interspeech 2019}},
page... | This paper describes our initial efforts to build a large-scale speaker
diarization (SD) and identification system on a recently digitized
radio broadcast archive from the Netherlands which has more than 6500
audio tapes with 3000 hours of Frisian-Dutch speech recorded between
1950–2016. The employed large-scale diariz... | 1906.07955 | title_snapshot |
dubey19_interspeech | Toeplitz Inverse Covariance Based Robust Speaker Clustering for Naturalistic Audio Streams | [
"Harishchandra Dubey",
"Abhijeet Sangwan",
"John H.L. Hansen"
] | https://www.isca-archive.org/interspeech_2019/dubey19_interspeech.html | https://www.isca-archive.org/interspeech_2019/dubey19_interspeech.pdf | 10.21437/Interspeech.2019-1102 | 416-420 | @inproceedings{dubey19_interspeech,
title = {{Toeplitz Inverse Covariance Based Robust Speaker Clustering for Naturalistic Audio Streams}},
author = {Harishchandra Dubey and Abhijeet Sangwan and John H.L. Hansen},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {416--420},
doi ... | Speaker diarization determines who spoke and when? in an audio stream.
In this study, we propose a model-based approach for robust speaker
clustering using i-vectors. The i-vectors extracted from different
segments of same speaker are correlated. We model this correlation
with a Markov Random Field (MRF) network. Leve... | 1907.05584 | title_snapshot |
kovacs19_interspeech | Examining the Combination of Multi-Band Processing and Channel Dropout for Robust Speech Recognition | [
"György Kovács",
"László Tóth",
"Dirk Van Compernolle",
"Marcus Liwicki"
] | https://www.isca-archive.org/interspeech_2019/kovacs19_interspeech.html | https://www.isca-archive.org/interspeech_2019/kovacs19_interspeech.pdf | 10.21437/Interspeech.2019-3215 | 421-425 | @inproceedings{kovacs19_interspeech,
title = {{Examining the Combination of Multi-Band Processing and Channel Dropout for Robust Speech Recognition}},
author = {György Kovács and László Tóth and Dirk Van Compernolle and Marcus Liwicki},
year = {2019},
booktitle = {{Interspeech 2019}},
pages ... | A pivotal question in Automatic Speech Recognition (ASR) is the robustness
of the trained models. In this study, we investigate the combination
of two methods commonly applied to increase the robustness of ASR systems.
On the one hand, inspired by auditory experiments and signal processing
considerations, multi-band ba... | null | null |
soni19_interspeech | Label Driven Time-Frequency Masking for Robust Continuous Speech Recognition | [
"Meet Soni",
"Ashish Panda"
] | https://www.isca-archive.org/interspeech_2019/soni19_interspeech.html | https://www.isca-archive.org/interspeech_2019/soni19_interspeech.pdf | 10.21437/Interspeech.2019-2172 | 426-430 | @inproceedings{soni19_interspeech,
title = {{Label Driven Time-Frequency Masking for Robust Continuous Speech Recognition}},
author = {Meet Soni and Ashish Panda},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {426--430},
doi = {10.21437/Interspeech.2019-2172},
issn =... | The application of Time-Frequency (T-F) masking based approaches for
Automatic Speech Recognition has been shown to provide significant
gains in system performance in the presence of additive noise. Such
approaches give performance improvement when the T-F masking front-end
is trained jointly with the acoustic model. H... | null | null |
wu19c_interspeech | Speaker-Invariant Feature-Mapping for Distant Speech Recognition via Adversarial Teacher-Student Learning | [
"Long Wu",
"Hangting Chen",
"Li Wang",
"Pengyuan Zhang",
"Yonghong Yan"
] | https://www.isca-archive.org/interspeech_2019/wu19c_interspeech.html | https://www.isca-archive.org/interspeech_2019/wu19c_interspeech.pdf | 10.21437/Interspeech.2019-2136 | 431-435 | @inproceedings{wu19c_interspeech,
title = {{Speaker-Invariant Feature-Mapping for Distant Speech Recognition via Adversarial Teacher-Student Learning}},
author = {Long Wu and Hangting Chen and Li Wang and Pengyuan Zhang and Yonghong Yan},
year = {2019},
booktitle = {{Interspeech 2019}},
pages ... | Feature mapping (FM) jointly trained with acoustic model (AFM) is commonly
used for single-channel speech enhancement. However, the performance
is affected by the inter-speaker variability. In this paper, we propose
speaker-invariant AFM (SIAFM) aiming at curtailing the inter-talker
variability while achieving speech e... | null | null |
ming19_interspeech | Full-Sentence Correlation: A Method to Handle Unpredictable Noise for Robust Speech Recognition | [
"Ji Ming",
"Danny Crookes"
] | https://www.isca-archive.org/interspeech_2019/ming19_interspeech.html | https://www.isca-archive.org/interspeech_2019/ming19_interspeech.pdf | 10.21437/Interspeech.2019-2127 | 436-440 | @inproceedings{ming19_interspeech,
title = {{Full-Sentence Correlation: A Method to Handle Unpredictable Noise for Robust Speech Recognition}},
author = {Ji Ming and Danny Crookes},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {436--440},
doi = {10.21437/Interspeech.2019-21... | We describe the theory and implementation of full-sentence speech correlation
for speech recognition, and demonstrate its superior robustness to
unseen/untrained noise. For the Aurora 2 data, trained with only clean
speech, the new method performs competitively against the state-of-the-art
with multicondition training ... | null | null |
soni19b_interspeech | Generative Noise Modeling and Channel Simulation for Robust Speech Recognition in Unseen Conditions | [
"Meet Soni",
"Sonal Joshi",
"Ashish Panda"
] | https://www.isca-archive.org/interspeech_2019/soni19b_interspeech.html | https://www.isca-archive.org/interspeech_2019/soni19b_interspeech.pdf | 10.21437/Interspeech.2019-2090 | 441-445 | @inproceedings{soni19b_interspeech,
title = {{Generative Noise Modeling and Channel Simulation for Robust Speech Recognition in Unseen Conditions}},
author = {Meet Soni and Sonal Joshi and Ashish Panda},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {441--445},
doi = {10.214... | Multi-conditioned training is a state-of-the-art approach to achieve
robustness in Automatic Speech Recognition (ASR) systems. This approach
works well in practice for seen degradation conditions. However, the
performance of such system is still an issue for unseen degradation
conditions. In this work we consider disto... | null | null |
kumar19_interspeech | Far-Field Speech Enhancement Using Heteroscedastic Autoencoder for Improved Speech Recognition | [
"Shashi Kumar",
"Shakti P. Rath"
] | https://www.isca-archive.org/interspeech_2019/kumar19_interspeech.html | https://www.isca-archive.org/interspeech_2019/kumar19_interspeech.pdf | 10.21437/Interspeech.2019-2032 | 446-450 | @inproceedings{kumar19_interspeech,
title = {{Far-Field Speech Enhancement Using Heteroscedastic Autoencoder for Improved Speech Recognition}},
author = {Shashi Kumar and Shakti P. Rath},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {446--450},
doi = {10.21437/Interspeech.2... | Automatic speech recognition (ASR) systems trained on clean speech
do not perform well in far-field scenario. Degradation in word error
rate (WER) can be as large as 40% in this mismatched scenario. Typically,
speech enhancement is applied to map speech from far-field condition
to clean condition using a neural network... | null | null |
delcroix19_interspeech | End-to-End SpeakerBeam for Single Channel Target Speech Recognition | [
"Marc Delcroix",
"Shinji Watanabe",
"Tsubasa Ochiai",
"Keisuke Kinoshita",
"Shigeki Karita",
"Atsunori Ogawa",
"Tomohiro Nakatani"
] | https://www.isca-archive.org/interspeech_2019/delcroix19_interspeech.html | https://www.isca-archive.org/interspeech_2019/delcroix19_interspeech.pdf | 10.21437/Interspeech.2019-1856 | 451-455 | @inproceedings{delcroix19_interspeech,
title = {{End-to-End SpeakerBeam for Single Channel Target Speech Recognition}},
author = {Marc Delcroix and Shinji Watanabe and Tsubasa Ochiai and Keisuke Kinoshita and Shigeki Karita and Atsunori Ogawa and Tomohiro Nakatani},
year = {2019},
booktitle = {{Inte... | End-to-end (E2E) automatic speech recognition (ASR) that directly maps
a sequence of speech features into a sequence of characters using a
single neural network has received a lot of attention as it greatly
simplifies the training and decoding pipelines and enables optimizing
the whole system E2E. Recently, such system... | null | null |
hsu19_interspeech | NIESR: Nuisance Invariant End-to-End Speech Recognition | [
"I-Hung Hsu",
"Ayush Jaiswal",
"Premkumar Natarajan"
] | https://www.isca-archive.org/interspeech_2019/hsu19_interspeech.html | https://www.isca-archive.org/interspeech_2019/hsu19_interspeech.pdf | 10.21437/Interspeech.2019-1836 | 456-460 | @inproceedings{hsu19_interspeech,
title = {{NIESR: Nuisance Invariant End-to-End Speech Recognition}},
author = {I-Hung Hsu and Ayush Jaiswal and Premkumar Natarajan},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {456--460},
doi = {10.21437/Interspeech.2019-1836},
issn ... | Deep neural network models for speech recognition have achieved great
success recently, but they can learn incorrect associations between
the target and nuisance factors of speech (e.g., speaker identities,
background noise, etc.), which can lead to overfitting. While several
methods have been proposed to tackle this p... | 1907.03233 | title_snapshot |
suzuki19_interspeech | Knowledge Distillation for Throat Microphone Speech Recognition | [
"Takahito Suzuki",
"Jun Ogata",
"Takashi Tsunakawa",
"Masafumi Nishida",
"Masafumi Nishimura"
] | https://www.isca-archive.org/interspeech_2019/suzuki19_interspeech.html | https://www.isca-archive.org/interspeech_2019/suzuki19_interspeech.pdf | 10.21437/Interspeech.2019-1597 | 461-465 | @inproceedings{suzuki19_interspeech,
title = {{Knowledge Distillation for Throat Microphone Speech Recognition}},
author = {Takahito Suzuki and Jun Ogata and Takashi Tsunakawa and Masafumi Nishida and Masafumi Nishimura},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {461--465},
d... | Throat microphones are robust against external noise because they receive
vibrations directly from the skin, however, their available speech
data is limited. This work aims to improve the speech recognition accuracy
of throat microphones, and we propose a knowledge distillation method
of hybrid DNN-HMM acoustic model. ... | null | null |
wu19d_interspeech | Improved Speaker-Dependent Separation for CHiME-5 Challenge | [
"Jian Wu",
"Yong Xu",
"Shi-Xiong Zhang",
"Lianwu Chen",
"Meng Yu",
"Lei Xie",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2019/wu19d_interspeech.html | https://www.isca-archive.org/interspeech_2019/wu19d_interspeech.pdf | 10.21437/Interspeech.2019-1569 | 466-470 | @inproceedings{wu19d_interspeech,
title = {{Improved Speaker-Dependent Separation for CHiME-5 Challenge}},
author = {Jian Wu and Yong Xu and Shi-Xiong Zhang and Lianwu Chen and Meng Yu and Lei Xie and Dong Yu},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {466--470},
doi = ... | This paper summarizes several contributions for improving the speaker-dependent
separation system for CHiME-5 challenge, which aims to solve the problem
of multi-channel, highly-overlapped conversational speech recognition
in a dinner party scenario with reverberations and non-stationary noises.
Specifically, we adopt ... | 1904.03792 | title_snapshot |
wang19b_interspeech | Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling | [
"Peidong Wang",
"Ke Tan",
"DeLiang Wang"
] | https://www.isca-archive.org/interspeech_2019/wang19b_interspeech.html | https://www.isca-archive.org/interspeech_2019/wang19b_interspeech.pdf | 10.21437/Interspeech.2019-1495 | 471-475 | @inproceedings{wang19b_interspeech,
title = {{Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling}},
author = {Peidong Wang and Ke Tan and DeLiang Wang},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {471--475},
doi ... | Monaural speech enhancement has made dramatic advances in recent years.
Although enhanced speech has been demonstrated to have better intelligibility
and quality for human listeners, feeding it directly to automatic speech
recognition (ASR) systems trained with noisy speech has not produced
expected improvements in ASR... | 1903.04567 | title_snapshot |
wang19c_interspeech | Enhanced Spectral Features for Distortion-Independent Acoustic Modeling | [
"Peidong Wang",
"DeLiang Wang"
] | https://www.isca-archive.org/interspeech_2019/wang19c_interspeech.html | https://www.isca-archive.org/interspeech_2019/wang19c_interspeech.pdf | 10.21437/Interspeech.2019-1493 | 476-480 | @inproceedings{wang19c_interspeech,
title = {{Enhanced Spectral Features for Distortion-Independent Acoustic Modeling}},
author = {Peidong Wang and DeLiang Wang},
year = {2019},
booktitle = {{Interspeech 2019}},
pages = {476--480},
doi = {10.21437/Interspeech.2019-1493},
issn = ... | It has recently been shown that a distortion-independent acoustic modeling
method is able to overcome the distortion problem caused by speech
enhancement. In this study, we improve the distortion-independent acoustic
model by feeding it with enhanced spectral features. Using enhanced
magnitude spectra, the automatic sp... | null | null |
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