metadata
library_name: transformers
license: mit
datasets:
- NhutP/VSV-1100
- mozilla-foundation/common_voice_14_0
- AILAB-VNUHCM/vivos
language:
- vi
metrics:
- wer
base_model:
- openai/whisper-small
Introduction
- We release a new model for Vietnamese speech regconition task.
- We fine-tuned openai/whisper-small on our new dataset VSV-1100.
Training data
| VSV-1100 | T2S* | CMV14-vi | VIVOS | VLSP2021 | Total |
|---|---|---|---|---|---|
| 1100 hours | 11 hours | 3.04 hours | 13.94 hours | 180 hours | 1308 hours |
* We use a text-to-speech model to generate sentences containing words that do not appear in our dataset.
WER result
| CMV14-vi | VIVOS | VLSP2020-T1 | VLSP2020-T2 | VLSP2021-T1 | VLSP2021-T2 | Bud500 |
|---|---|---|---|---|---|---|
| 9.79 | 5.74 | 14.15 | 39.25 | 14 | 10.06 | 5.97 |
Usage
Inference
from transformers import WhisperProcessor, WhisperForConditionalGeneration
import librosa
# load model and processor
processor = WhisperProcessor.from_pretrained("NhutP/ViWhisper-small")
model = WhisperForConditionalGeneration.from_pretrained("NhutP/ViWhisper-small")
model.config.forced_decoder_ids = None
# load a sample
array, sampling_rate = librosa.load(...) # Load some
input_features = processor(array, sampling_rate=sampling_rate, return_tensors="pt").input_features
# generate token ids
predicted_ids = model.generate(input_features)
# decode token ids to text
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
Use with pipeline
from transformers import pipeline
pipe = pipeline(
"automatic-speech-recognition",
model="NhutP/ViWhisper-small",
max_new_tokens=128,
chunk_length_s=30,
return_timestamps=False,
device= '...' # 'cpu' or 'cuda'
)
output = pipe(path_to_audio_samplingrate_16000)['text']
Citation
@misc{VSV-1100,
author = {Pham Quang Nhut and Duong Pham Hoang Anh and Nguyen Vinh Tiep},
title = {VSV-1100: Vietnamese social voice dataset},
url = {https://github.com/NhutP/VSV-1100},
year = {2024}
}
Also, please give us a star on github: https://github.com/NhutP/ViWhisper if you find our project useful
Contact me at: [email protected] (Pham Quang Nhut)