RakhatM/medical_asr_aligned_27_04

Medical ASR Aligned Dataset

Aligned Kazakh medical speech dataset from the «ТЕЛЕДӘРІГЕР» (TeleDoctor) TV program on Qazaqstan National Channel.

Dataset Description

Audio-transcript aligned segments of Kazakh-language medical TV broadcasts. Each segment contains the original audio chunk, ASR transcription, human reference transcription, and Character Error Rate (CER).

Only segments with CER < 25% are included.

Stats

Split	Segments	Avg CER	Avg Duration	Total Duration
train	17,623	0.1011	15.1s	74.16h
dev	2,017	0.1027	15.0s	8.42h
test	2,366	0.1040	15.2s	9.98h
total	22,006	0.1015	15.1s	92.55h

Data Fields

• audio: Audio waveform (WAV, mono, 16kHz)
• asr_text: ASR transcription (Kazakh)
• human_text: Human reference transcription (Kazakh)
• cer: Character Error Rate between ASR and human text
• duration: Segment duration in seconds

How the Data Was Aligned

1. Source transcripts were taken from the transcripts ready folder, which contained speaker-diarized transcripts from Whisper AI Scribe.
2. Preprocessing: metadata headers (Title, Created, Profile, Speakers), timestamp lines, and speaker labels were stripped. The remaining text was concatenated into plain text per episode.
3. Audio conversion: all audio files were converted to WAV mono 16kHz.
4. Alignment: the EuroSpeech alignment pipeline (parliament_transcript_aligner) was used to align ASR output against human transcripts. The pipeline segments audio into 10–20s windows, runs ASR (model: issai/whisper-tilsync-09oct2025, language: kk), and aligns ASR segments to reference text using CER-based matching.
5. Filtering: only segments with CER < 0.25 were retained.
6. Splitting: episodes were randomly split 80/10/10 into train/dev/test (seed=42) before alignment.