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| from transformers import pipeline | |
| import gradio as gr | |
| titulo = "Mi primer demo de Transcripción" | |
| descripcion = "Este es un demo transcriptor audio-texto en español." | |
| modelo = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-xlsr-53-spanish") | |
| def transcribe(audio): | |
| text = modelo(audio)["text"] | |
| return text | |
| gr.Interface( | |
| fn=transcribe, | |
| inputs=[gr.Audio(source="microphone", type="filepath")], | |
| outputs=["textbox"], | |
| title = titulo, | |
| description = descripcion | |
| ).launch() |