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| from transformers import pipeline | |
| import gradio as gr | |
| import time | |
| p = pipeline("automatic-speech-recognition", model="openai/whisper-base", generate_kwargs={"language": "|en|", "task": "transcribe"}) | |
| def transcribe(audio, state=""): | |
| time.sleep(2) | |
| text = p(audio)["text"] | |
| state += text + " " | |
| return state, state | |
| gr.Interface( | |
| fn=transcribe, | |
| inputs=[ | |
| gr.inputs.Audio(source="microphone", type="filepath"), | |
| "state" | |
| ], | |
| outputs=[ | |
| "textbox", | |
| "state" | |
| ], | |
| live=True).launch() |