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import torch
from transformers import pipeline
import numpy as np
import gradio as gr
pipe = pipeline(
"automatic-speech-recognition", model="openai/whisper-base"
)
def transcribe(audio):
sr, y = audio
y = y.astype(np.float32)
y /= np.max(np.abs(y))
return pipe({"sampling_rate": sr, "raw": y})["text"]
demo = gr.Interface(
transcribe,
gr.Audio(sources=["microphone"]),
"text",
)
demo.launch() |