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import gradio as gr | |
from transformers import pipeline | |
import numpy as np | |
transcriber = pipeline( | |
"automatic-speech-recognition", | |
model="model", | |
chunk_length_s=30 | |
) | |
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(), | |
"text", | |
title = "Banking-ASR", | |
description = "Please record/upload Banking Queries to Transcribe", | |
theme=gr.themes.Soft() | |
) | |
demo.launch() |