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