File size: 1,141 Bytes
e5e9b34 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
import librosa
import torch
from transformers import Wav2Vec2ForCTC, AutoProcessor
from transformers import set_seed
def transcribe(fp:str, target_lang:str) -> str:
'''
For given audio file, transcribe it.
Parameters
----------
fp: str
The file path to the audio file.
target_lang:str
The ISO-3 code of the target language.
Returns
----------
transcript:str
The transcribed text.
'''
# Ensure replicability
set_seed(555)
# Load transcription model
model_id = "facebook/mms-1b-all"
target_lang = "mos"
processor = AutoProcessor.from_pretrained(model_id, target_lang=target_lang)
model = Wav2Vec2ForCTC.from_pretrained(model_id, target_lang=target_lang, ignore_mismatched_sizes=True)
# Process the audio
signal, sampling_rate = librosa.load(fp, sr=16000)
inputs = processor(signal, sampling_rate=16_000, return_tensors="pt")
# Inference
with torch.no_grad():
outputs = model(**inputs).logits
ids = torch.argmax(outputs, dim=-1)[0]
transcript = processor.decode(ids)
return transcript |