| import gradio as gr | |
| from transformers import pipeline | |
| # Cargar el modelo de transcripci贸n Whisper | |
| transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-small") | |
| # Funci贸n para transcribir audio | |
| def transcribe(audio): | |
| result = transcriber(audio) | |
| return result["text"] | |
| # Crear interfaz Gradio | |
| demo = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio(source="upload", type="filepath"), | |
| outputs="text", | |
| title="Transcripci贸n de Audio en Vivo", | |
| description="Sube un archivo de audio para transcribir su contenido autom谩ticamente." | |
| ) | |
| # Lanzar la aplicaci贸n | |
| if __name__ == "__main__": | |
| demo.launch() |