app.py

import gradio as gr
from transformers import pipeline
import numpy as np

title = "Frisian Automatic Speech Recognition"
transcriber = pipeline("automatic-speech-recognition", model="Reihaneh/wav2vec2_frisian_common_voice_1")

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=["upload"]),
    "text",
    #fn=transcribe,
    #inputs=gr.Audio(sources=["upload"]),
    #outputs="text",
    title=title,
)

demo.launch(debug=True)