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--- |
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language: |
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- nl |
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tags: |
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- automatic-speech-recognition |
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- hf-asr-leaderboard |
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- model_for_talk |
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- mozilla-foundation/common_voice_8_0 |
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- nl |
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- robust-speech-event |
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- vl |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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- multilingual_librispeech |
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model-index: |
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- name: xls-r-nl-v1-cv8-lm |
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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: nl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 6.69 |
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- name: Test CER |
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type: cer |
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value: 1.97 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: nl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 20.79 |
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- name: Test CER |
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type: cer |
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value: 10.72 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: nl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 19.71 |
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--- |
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# XLS-R-based CTC model with 5-gram language model from Common Voice |
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This model is a version of [facebook/wav2vec2-xls-r-2b-22-to-16](https://huggingface.co/facebook/wav2vec2-xls-r-2b-22-to-16) fine-tuned mainly on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - NL dataset (see details below), on which a small 5-gram language model is added based on the Common Voice training corpus. This model achieves the following results on the evaluation set (of Common Voice 8.0): |
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- Wer: 0.0669 |
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- Cer: 0.0197 |
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## Model description |
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The model takes 16kHz sound input, and uses a Wav2Vec2ForCTC decoder with 48 letters to output the final result. |
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To improve accuracy, a beam decoder is used; the beams are scored based on 5-gram language model trained on the Common Voice 8 corpus. |
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## Intended uses & limitations |
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This model can be used to transcribe Dutch or Flemish spoken dutch to text (without punctuation). |
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## Training and evaluation data |
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0. The model was initialized with [the 2B parameter model from Facebook](facebook/wav2vec2-xls-r-2b-22-to-16). |
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1. The model was then trained `2000` iterations (batch size 32) on [the `dutch` configuration of the `multilingual_librispeech` dataset](https://huggingface.co/datasets/multilingual_librispeech/). |
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1. The model was then trained `2000` iterations (batch size 32) on [the `nl` configuration of the `common_voice_8_0` dataset](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0). |
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2. The model was then trained `6000` iterations (batch size 32) on [the `cgn` dataset](https://taalmaterialen.ivdnt.org/download/tstc-corpus-gesproken-nederlands/). |
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3. The model was then trained `6000` iterations (batch size 32) on [the `nl` configuation of the `common_voice_8_0` dataset](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0). |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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