readme: 
  ---
  language:
  - multilingual
  - ar
  - as
  - br
  - ca
  - cnh
  - cs
  - cv
  - cy
  - de
  - dv
  - el
  - en
  - eo
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - hi
  - hsb
  - hu
  - ia
  - id
  - ja
  - ka
  - ky
  - lg
  - lt
  - ly
  - mn
  - mt
  - nl
  - or
  - pl
  - pt
  - ro
  - ru
  - sah
  - sl
  - ta
  - th
  - tr
  - tt
  - uk
  - vi
  license: apache-2.0
  tags:
  - audio
  - automatic-speech-recognition
  - hf-asr-leaderboard
  - robust-speech-event
  - speech
  - xlsr-fine-tuning-week
  datasets:
  - common_voice
  language_bcp47:
  - fy-NL
  - ga-IE
  - pa-IN
  - rm-sursilv
  - rm-vallader
  - sy-SE
  - zh-CN
  - zh-HK
  - zh-TW
  model-index:
  - name: XLSR Wav2Vec2 for 56 language by Voidful
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        name: Common Voice
        type: common_voice
      metrics:
      - type: cer
        value: 23.21
        name: Test CER
  ---
  
  # Model Card for wav2vec2-xlsr-multilingual-56
   
   
  # Model Details
   
  ## Model Description
   
  - **Developed by:** voidful
  - **Shared by [Optional]:** Hugging Face
  - **Model type:** automatic-speech-recognition
  - **Language(s) (NLP):** multilingual (*56 language, 1 model Multilingual ASR*)
  - **License:** Apache-2.0
  - **Related Models:**
    - **Parent Model:** wav2vec
  - **Resources for more information:** 
      - [GitHub Repo](https://github.com/voidful/wav2vec2-xlsr-multilingual-56)
   	- [Model Space](https://huggingface.co/spaces/Kamtera/Persian_Automatic_Speech_Recognition_and-more)
   
   
  # Uses
   
   
  ## Direct Use
   
  This model can be used for the task of automatic-speech-recognition
   
  ## Downstream Use [Optional]
   
  More information needed
   
  ## Out-of-Scope Use
   
  The model should not be used to intentionally create hostile or alienating environments for people.
   
  # Bias, Risks, and Limitations
   
  Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
   
   
  ## Recommendations
   
  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
   
   
  # Training Details
   
  ## Training Data
   
  See the [common_voice dataset card](https://huggingface.co/datasets/common_voice)
  Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on 56 language using the [Common Voice](https://huggingface.co/datasets/common_voice).  
   
  ## Training Procedure
   
   
  ### Preprocessing
   
  More information needed
   
  ### Speeds, Sizes, Times
   
   
  When using this model, make sure that your speech input is sampled at 16kHz.
   
   
  # Evaluation
   
   
  ## Testing Data, Factors & Metrics
   
  ### Testing Data
   
  More information needed
   
  ### Factors
   
   
  ### Metrics
   
  More information needed
  ## Results 
  <details>
   <summary> Click to expand </summary>
   
  | Common Voice Languages | Num. of data | Hour   | WER    | CER   |
  |------------------------|--------------|--------|--------|-------|
  | ar                     | 21744        | 81.5   | 75.29  | 31.23 |
  | as                     | 394          | 1.1    | 95.37  | 46.05 |
  | br                     | 4777         | 7.4    | 93.79  | 41.16 |
  | ca                     | 301308       | 692.8  | 24.80  | 10.39 |
  | cnh                    | 1563         | 2.4    | 68.11  | 23.10 |
  | cs                     | 9773         | 39.5   | 67.86  | 12.57 |
  | cv                     | 1749         | 5.9    | 95.43  | 34.03 |
  | cy                     | 11615        | 106.7  | 67.03  | 23.97 |
  | de                     | 262113       | 822.8  | 27.03  | 6.50  |
  | dv                     | 4757         | 18.6   | 92.16  | 30.15 |
  | el                     | 3717         | 11.1   | 94.48  | 58.67 |
  | en                     | 580501       | 1763.6 | 34.87  | 14.84 |
  | eo                     | 28574        | 162.3  | 37.77  | 6.23  |
  | es                     | 176902       | 337.7  | 19.63  | 5.41  |
  | et                     | 5473         | 35.9   | 86.87  | 20.79 |
  | eu                     | 12677        | 90.2   | 44.80  | 7.32  |
  | fa                     | 12806        | 290.6  | 53.81  | 15.09 |
  | fi                     | 875          | 2.6    | 93.78  | 27.57 |
  | fr                     | 314745       | 664.1  | 33.16  | 13.94 |
  | fy-NL                  | 6717         | 27.2   | 72.54  | 26.58 |
  | ga-IE                  | 1038         | 3.5    | 92.57  | 51.02 |
  | hi                     | 292          | 2.0    | 90.95  | 57.43 |
  | hsb                    | 980          | 2.3    | 89.44  | 27.19 |
  | hu                     | 4782         | 9.3    | 97.15  | 36.75 |
  | ia                     | 5078         | 10.4   | 52.00  | 11.35 |
  | id                     | 3965         | 9.9    | 82.50  | 22.82 |
  | it                     | 70943        | 178.0  |