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import gradio as gr
from transformers import pipeline
import numpy as np
transcriber = pipeline("automatic-speech-recognition", model="Oysiyl/w2v-bert-2.0-ukrainian-colab-CV16.0")
def transcribe(audio):
sr, y = audio
y = y.astype(np.float32)
y /= np.max(np.abs(y))
return transcriber({"sampling_rate": sr, "raw": y})["text"]
demo = gr.Interface(
transcribe,
gr.Audio(sources=["microphone", "upload"]),
outputs="text",
title="Automatic Speech Recognition for Ukrainian language demo",
description="Say something or upload audiofile!",
examples=[["examples/asr_example.wav"]],
cache_examples=True
)
demo.launch() |