Instructions to use YosefA/wave2vec2_amharic_stt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use YosefA/wave2vec2_amharic_stt with speechbrain:
from speechbrain.pretrained import EncoderASR model = EncoderASR.from_hparams( "YosefA/wave2vec2_amharic_stt" ) model.transcribe_file("file.wav") - Notebooks
- Google Colab
- Kaggle
Amharic Speech-to-Text Transcription Model
This model transcribes Amharic speech to text. It's built on Facebook's Wav2Vec2 and trained using SpeechBrain.
Intended Use
Its main purpose is to transcribe audio from Instagram, YouTube, and TikTok video content for further analysis (e.g., trend identification, content moderation).
Limitations
Performance may vary with audio quality, background noise, and informal speech commonly found in social media.
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