Solvve / ml_speech2text_voice_denoiser

Review of Speech to text voice denoisers

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Speech2text & Denoise

License Python 3.7 scikit-learn 0.23.2 torch 0.23.2 Solvve

Description

Speech to text & Denoiser using Wav2Vec pretrained model. Denoiser using Dual-signal Transformation LSTM Network. Fine-Tune Wav2Vec2 model

We follow the next steps:

  1. Data preparation
  2. Data preprocessing
  3. Modeling with Wav2Vec2 model
  4. Modeling after denoise
  5. Fine-tune Wav2Vec multi-language ASR

From Wec2Vec2_Denoise.ipynb:

Levenshtein metrics Mean Median
Word Error Rate 0.26 0.20
Match Error Rate 0.25 0.2
Word Information Lost 0.40 0.36

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Review of Speech to text voice denoisers


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Language:Jupyter Notebook 100.0%