| import gradio as gr |
| from transformers import pipeline |
| import numpy as np |
|
|
| transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en") |
|
|
| def transcribe(stream, new_chunk): |
| sr, y = new_chunk |
| y = y.astype(np.float32) |
| y /= np.max(np.abs(y)) |
|
|
| if stream is not None: |
| stream = np.concatenate([stream, y]) |
| else: |
| stream = y |
| return stream, transcriber({"sampling_rate": sr, "raw": stream})["text"] |
|
|
|
|
| demo = gr.Interface( |
| transcribe, |
| ["state", gr.Audio(sources=["microphone"], streaming=True)], |
| ["state", "text"], |
| live=True, |
| ) |
|
|
| demo.launch() |
|
|
