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import gradio as gr
from transformers import pipeline
import numpy as np
transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.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(
fn=transcribe,
inputs = gr.Audio(sources=["microphone"], streaming=True),
outputs = gr.outputs.Textbox(),
live=True,
)
demo.launch(debug=True, share=True) |