
# Wav2vec2 Large 100k Voxpopuli fine-tuned with Common Voice and TTS-Portuguese Corpus in Portuguese 

[Wav2vec2 Large 100k Voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) fine-tuned in Portuguese using the Common Voice 7.0 and TTS-Portuguese Corpus.



# Use this model

```python

from transformers import AutoTokenizer, Wav2Vec2ForCTC
  
tokenizer = AutoTokenizer.from_pretrained("Edresson/wav2vec2-large-100k-voxpopuli-ft-Common-Voice_plus_TTS-Dataset-portuguese")

model = Wav2Vec2ForCTC.from_pretrained("Edresson/wav2vec2-large-100k-voxpopuli-ft-Common-Voice_plus_TTS-Dataset-portuguese")
```
# Results
For the results check the [paper](https://arxiv.org/abs/2204.00618)

# Example test with Common Voice Dataset


```python
dataset = load_dataset("common_voice", "pt", split="test", data_dir="./cv-corpus-6.1-2020-12-11")

resampler = torchaudio.transforms.Resample(orig_freq=48_000, new_freq=16_000)

def map_to_array(batch):
    speech, _ = torchaudio.load(batch["path"])
    batch["speech"] = resampler.forward(speech.squeeze(0)).numpy()
    batch["sampling_rate"] = resampler.new_freq
    batch["sentence"] = re.sub(chars_to_ignore_regex, '', batch["sentence"]).lower().replace("â€™", "'")
    return batch
```

```python
ds = dataset.map(map_to_array)
result = ds.map(map_to_pred, batched=True, batch_size=1, remove_columns=list(ds.features.keys()))
print(wer.compute(predictions=result["predicted"], references=result["target"]))
```


{"language": "pt", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "pt", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "PyTorch"], "datasets": ["Common Voice"], "metrics": ["wer"]}
transformers pytorch wav2vec2 automatic-speech-recognition audio speech pt portuguese-speech-corpus PyTorch arxiv:2204.00618 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #pt #portuguese-speech-corpus #PyTorch #arxiv-2204.00618 #license-apache-2.0 #model-index #endpoints_compatible #region-us 


# Wav2vec2 Large 100k Voxpopuli fine-tuned with Common Voice and TTS-Portuguese Corpus in Portuguese 

Wav2vec2 Large 100k Voxpopuli fine-tuned in Portuguese using the Common Voice 7.0 and TTS-Portuguese Corpus.



# Use this model


# Results
For the results check the paper

# Example test with Common Voice Dataset







# Wav2vec2 Large 100k Voxpopuli fine-tuned with Common Voice and TTS-Portuguese Corpus in Portuguese 

Wav2vec2 Large 100k Voxpopuli fine-tuned in Portuguese using the Common Voice 7.0 and TTS-Portuguese Corpus. # Use this model # Results
For the results check the paper # Example test with Common Voice Dataset
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #pt #portuguese-speech-corpus #PyTorch #arxiv-2204.00618 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 # Wav2vec2 Large 100k Voxpopuli fine-tuned with Common Voice and TTS-Portuguese Corpus in Portuguese 

Wav2vec2 Large 100k Voxpopuli fine-tuned in Portuguese using the Common Voice 7.0 and TTS-Portuguese Corpus. # Use this model # Results
For the results check the paper # Example test with Common Voice Dataset
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #pt #portuguese-speech-corpus #PyTorch #arxiv-2204.00618 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
# Wav2vec2 Large 100k Voxpopuli fine-tuned with Common Voice and TTS-Portuguese Corpus in Portuguese 

Wav2vec2 Large 100k Voxpopuli fine-tuned in Portuguese using the Common Voice 7.0 and TTS-Portuguese Corpus.# Use this model# Results
For the results check the paper# Example test with Common Voice Dataset