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import gradio as gr | |
from transformers import pipeline | |
# Load Wav2Vec 2.0 speech recognition model | |
asr = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h") | |
# Function to process audio and return transcribed text | |
def transcribe(audio): | |
if audio is None: | |
return "No audio provided." | |
return asr(audio)["text"] | |
# Gradio Interface | |
interface = gr.Interface( | |
fn=transcribe, | |
inputs=gr.Audio(type="filepath", label="Upload or Record Audio"), | |
outputs=gr.Textbox(label="Transcribed Text"), | |
title="🎤 Wav2Vec 2.0 - Speech to Text", | |
description="Upload or record an audio file and get the transcribed text using Facebook's Wav2Vec 2.0." | |
) | |
interface.launch() | |