readme: ---
  license: gpl-3.0
  
  language:
  - be
  
  tags:
  - audio
  - speech
  - automatic-speech-recognition
  
  datasets:
  - mozilla-foundation/common_voice_8_0
  
  metrics:
  - wer
  
  model-index:
  - name: wav2vec2
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: be
      metrics:
      - name: Dev WER
        type: wer
        value: 17.61
      - name: Test WER
        type: wer
        value: 18.7
      - name: Dev WER (with LM)
        type: wer
        value: 11.5
      - name: Test WER (with LM)
        type: wer
        value: 12.4
  ---
  
  # Automatic Speech Recognition for Belarusian language
  
  Fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on `mozilla-foundation/common_voice_8_0 be` dataset.
  
  `Train`, `Dev`, `Test` splits were used as they are present in the dataset. No additional data was used from `Validated` split, 
  only 1 voicing of each sentence was used - the way the data was split by [CommonVoice CorporaCreator](https://github.com/common-voice/CorporaCreator). 
  To build a better model **one can use additional voicings from `Validated` split** for sentences already present in `Train`, `Dev`, `Test` splits,
  i.e. enlarge mentioned splits.
  
  Language model was built using [KenLM](https://kheafield.com/code/kenlm/estimation/). 
  5-gram Language model was built on sentences from `Train + (Other - Dev - Test)` splits of `mozilla-foundation/common_voice_8_0 be` dataset.
  
  Source code is available [here](https://github.com/yks72p/stt_be).
  
  ## Run model in a browser
  
  This page contains interactive demo widget that lets you test this model right in a browser.
  
  However, this widget uses Acoustic model only **without** Language model that significantly improves overall performance.
  
  You can play with **full pipeline of Acoustic model + Language model** on the following [spaces page](https://huggingface.co/spaces/ales/wav2vec2-cv-be-lm)
  (also works from browser).
  