Fine-Tune Wav2Vec2 large model for English ASR
Data for fine-tune
Dataset |
Duration in hours |
Common Voice |
1667 |
Europarl |
85 |
How2 |
356 |
Librispeech |
936 |
MuST-C v1 |
407 |
MuST-C v2 |
482 |
Tedlium |
482 |
Evaluation result
Dataset |
Duration in hours |
WER w/o LM |
WER with LM |
Librispeech |
5.4 |
2.9 |
1.1 |
Tedlium |
2.6 |
7.9 |
5.4 |
Usage
from transformers.file_utils import cached_path, hf_bucket_url
from importlib.machinery import SourceFileLoader
from transformers import Wav2Vec2ProcessorWithLM
from IPython.lib.display import Audio
import torchaudio
import torch
model_name = "nguyenvulebinh/iwslt-asr-wav2vec-large-4500h"
model = SourceFileLoader("model", cached_path(hf_bucket_url(model_name,filename="model_handling.py"))).load_module().Wav2Vec2ForCTC.from_pretrained(model_name)
processor = Wav2Vec2ProcessorWithLM.from_pretrained(model_name)
audio, sample_rate = torchaudio.load(cached_path(hf_bucket_url(model_name, filename="tst_2010_sample.wav")))
input_data = processor.feature_extractor(audio[0], sampling_rate=16000, return_tensors='pt')
output = model(**input_data)
print(processor.tokenizer.decode(output.logits.argmax(dim=-1)[0].detach().cpu().numpy()))
print(processor.decode(output.logits.cpu().detach().numpy()[0], beam_width=100).text)
Model Parameters License
The ASR model parameters are made available for non-commercial use only, under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. You can find details at: https://creativecommons.org/licenses/by-nc/4.0/legalcode
Contact
nguyenvulebinh@gmail.com