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import gradio as gr
from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
import torch
# Load the model and processor
processor = Wav2Vec2Processor.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn")
model = Wav2Vec2ForCTC.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn")
# Function to transcribe the audio
def transcribe_audio(audio):
input_values = processor(audio["array"], sampling_rate=audio["sampling_rate"], return_tensors="pt").input_values
# Inference
with torch.no_grad():
logits = model(input_values).logits
# Decode the transcription
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(predicted_ids)
return transcription[0] # Since we're only handling one audio file
# Set up the Gradio interface
interface = gr.Interface(
fn=transcribe_audio,
inputs=gr.Audio(source="microphone", type="filepath"), # Accept audio files
outputs="text",
title="Chinese Audio Transcription",
description="Upload or record an audio file to transcribe it into Chinese."
)
# Launch the interface
interface.launch()
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