readme: ---
  license: cc-by-4.0
  tags:
  - audio
  - automatic-speech-recognition
  - hf-asr-leaderboard
  language: et
  model-index:
  - name: xls-r-300m-et
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 
        type: common_voice
        args: et
      metrics:
      - name: Test WER
        type: wer
        value: 12.520395591222402
      - name: Test CER
        type: cer
        value: 2.7091152438624897
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: et
      metrics:
      - name: Test WER
        type: wer
        value: 13.38447882323104
      - name: Test CER
        type: cer
        value: 2.9816686199500255
  ---
  
  
  # XLS-R-300m-ET
  
  This is a XLS-R-300M model [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) finetuned on around 800 hours of diverse Estonian data.
  
  ## Model description
  This is a general-purpose Estonian ASR model trained in the Lab of Language Technology at TalTech. It consists of only the CTC-based end-to-end model, no language model is currently provided.
  
  ## Intended uses & limitations
  
  This model is intended for general-purpose speech recognition, such as broadcast conversations, interviews, talks, etc.
  
  ## How to use
  
  
  TODO
  
  #### Limitations and bias
  
  Since this model was trained on mostly broadcast speech and texts from the web, it might have problems correctly decoding the following:
    * Speech containing technical and other domain-specific terms
    * Children's speech
    * Non-native speech
    * Speech recorded under very noisy conditions or with a microphone far from the speaker
    * Very spontaneous and overlapping speech
  
  ## Training data
  Acoustic training data:
  
  | Type                  | Amount (h) |
  |-----------------------|:------:|
  | Broadcast speech      |   591  |
  | Spontaneous speech    |   53   |
  | Elderly speech corpus |   53   |
  | Talks, lectures       |   49   |
  | Parliament speeches   |   31   |
  | *Total*               |   *761*  |
  
  
  ## Training procedure
  
  Finetuned using Fairseq.
  
  ## Evaluation results
  
  ### WER
  
  |Dataset | WER |
  |---|---|
  | jutusaated.devset | 7.9 |
  | jutusaated.testset | 6.1 |
  | Common Voice 6.1 | 12.5 |
  | Common Voice 8.0 | 13.4 |
  