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import soundfile as sf
import librosa
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import gradio as gr
import os
api_token = os.getenv("API_TOKEN")
model_name = "indonesian-nlp/wav2vec2-indonesian-javanese-sundanese"
processor = Wav2Vec2Processor.from_pretrained(model_name, use_auth_token=api_token)
model = Wav2Vec2ForCTC.from_pretrained(model_name, use_auth_token=api_token)
device = "cuda" if torch.cuda.is_available() else "cpu"
model = model.to(device)
def convert(inputfile, outfile):
target_sr = 16000
data, sample_rate = librosa.load(inputfile)
data = librosa.resample(data, orig_sr=sample_rate, target_sr=target_sr)
sf.write(outfile, data, target_sr)
def parse_transcription(wav_file):
filename = wav_file.name.split('.')[0]
convert(wav_file.name, filename + "16k.wav")
speech, _ = sf.read(filename + "16k.wav")
input_values = processor(speech, sampling_rate=16_000, return_tensors="pt").input_values
input_values = input_values.to(device)
logits = model(input_values).logits
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.decode(predicted_ids[0], skip_special_tokens=True)
return transcription
output = gr.outputs.Textbox(label="The transcript")
input_ = gr.inputs.Audio(source="microphone", type="file")
gr.Interface(parse_transcription, inputs=input_, outputs=[output],
analytics_enabled=False,
title="Multilingual Speech Recognition for Indonesian Languages",
description="Automatic Speech Recognition Live Demo for Indonesian, Javanese and Sundanese Language",
article="This demo was built for the project "
"<a href='https://github.com/indonesian-nlp/multilingual-asr' target='_blank'>Multilingual Speech Recognition for Indonesian Languages</a>. "
"It uses the <a href='https://huggingface.co/indonesian-nlp/wav2vec2-indonesian-javanese-sundanese' target='_blank'>indonesian-nlp/wav2vec2-indonesian-javanese-sundanese</a> model "
"which was fine-tuned on Indonesian Common Voice, Javanese and Sundanese OpenSLR speech datasets."
).launch( inline=False, server_name="0.0.0.0", show_tips=False, enable_queue=True)
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