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Distil Wav2vec2
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Distil Wav2vec2
Developed by OthmaneJ
Distil-wav2vec2 is a distilled version of the wav2vec2 model, with a 45% reduction in size and a two-fold increase in inference speed, suitable for automatic speech recognition tasks.
Downloads 854
Release Time : 3/2/2022
Model Overview
This model is a lightweight version of the wav2vec2 model, focusing on automatic speech recognition tasks, achieving a smaller model size and faster inference speed through distillation techniques.
Model Features
Lightweight
The model size is 45% smaller than the original wav2vec2 base model, making it more suitable for resource-constrained environments.
Efficient Inference
Inference speed is doubled, with CPU time at 0.4006 seconds and GPU time at 0.0046 seconds (with a batch size of 64).
Balanced Performance
Maintains a relatively low word error rate while significantly improving operational efficiency.
Model Capabilities
English Speech Recognition
Audio-to-Text Conversion
Use Cases
Speech Transcription
Meeting Minutes
Automatically transcribe meeting recordings into text
Word error rate on Librispeech-test-clean is 0.0983
Voice Assistant
Used as the speech recognition module for lightweight voice assistants
Achieves fast response on resource-constrained devices
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