| import whisper | |
| import gradio as gr | |
| model = whisper.load_hf_model(repo_id="jerpint/whisper", filename="base.pt") | |
| def transcribe(audio, translate): | |
| task = "translate" if translate else None | |
| result = model.transcribe(audio, task=task) | |
| return result["text"] | |
| title = "BabelFish" | |
| description = "Record your voice in any language, babelfish will output a transcript of what was said. Check 'Translate to english' to get an english transcription. Based on the OpenAI Whisper model" | |
| gr.Interface( | |
| fn=transcribe, | |
| inputs=[ | |
| gr.Audio(source="microphone", type="filepath"), | |
| gr.Checkbox(label="Translate to english"), | |
| ], | |
| title=title, | |
| description=description, | |
| examples=[ | |
| ["samples/french_hello.wav", True], | |
| ["samples/english_hello.wav", True], | |
| ["samples/hebrew_hello.wav", True], | |
| ["samples/spanish_hello.wav", True], | |
| ], | |
| outputs="text", | |
| ).launch() | |