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--- |
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language: es |
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datasets: |
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- common_voice |
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metrics: |
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- wer |
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- cer |
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tags: |
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- audio |
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- automatic-speech-recognition |
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- speech |
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- xlsr-fine-tuning-week |
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license: apache-2.0 |
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--- |
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# Wav2Vec2-Large-XLSR-53-Spanish-With-LM |
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This is a model copy of [Wav2Vec2-Large-XLSR-53-Spanish](https://huggingface.co./jonatasgrosman/wav2vec2-large-xlsr-53-spanish) |
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that has language model support. |
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This model card can be seen as a demo for the [pyctcdecode](https://github.com/kensho-technologies/pyctcdecode) integration |
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with Transformers led by [this PR](https://github.com/huggingface/transformers/pull/14339). The PR explains in-detail how the |
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integration works. |
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In a nutshell: This PR adds a new Wav2Vec2WithLMProcessor class as drop-in replacement for Wav2Vec2Processor. |
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The only change from the existing ASR pipeline will be: |
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```diff |
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import torch |
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import torchaudio.functional as F |
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-from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor |
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+from transformers import Wav2Vec2ForCTC, Wav2Vec2ProcessorWithLM |
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from datasets import load_dataset |
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ds = load_dataset("common_voice", "es", split="test", streaming=True) |
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sample = next(iter(ds)) |
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resampled_audio = F.resample(torch.tensor(sample["audio"]["array"]), 48_000, 16_000).n |
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model = Wav2Vec2ForCTC.from_pretrained("patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm") |
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-processor = Wav2Vec2Processor.from_pretrained("patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm") |
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+processor = Wav2Vec2ProcessorWithLM.from_pretrained("patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm") |
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input_values = processor(resampled_audio, return_tensors="pt").input_values |
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with torch.no_grad(): |
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logits = model(input_values).logits |
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-prediction_ids = torch.argmax(logits, dim=-1) |
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-transcription = processor.batch_decode(prediction_ids) |
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+transcription = processor.batch_decode(logits.cpu().numpy()).text |
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print(transcription) |
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``` |
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**Improvement** |
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This model has been compared on 512 speech samples from the Spanish Common Voice Test set and |
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gives a nice *20 %* performance boost: |
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The results can be reproduced by running *from this model repository*: |
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| Model | WER | CER | |
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| ------------- | ------------- | ------------- | |
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| patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm | **8.44%** | **2.93%** | |
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| jonatasgrosman/wav2vec2-large-xlsr-53-spanish | **10.20%** | **3.24%** | |
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``` |
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bash run_ngram_wav2vec2.py 1 512 |
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``` |
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``` |
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bash run_ngram_wav2vec2.py 0 512 |
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``` |
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with `run_ngram_wav2vec2.py` being |
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https://huggingface.co./patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm/blob/main/run_ngram_wav2vec2.py |
