app.py

import gradio as gr
from transformers import pipeline
import librosa

# Initialize the ASR model
asr_model = pipeline("automatic-speech-recognition", model="openai/whisper-small")

def transcribe(file_path):
    # Load the audio file with librosa
    data, samplerate = librosa.load(file_path, sr=None)
    # Pass the audio data to the model for transcription without specifying sampling_rate
    transcription = asr_model(data)
    return transcription["text"]

# Create the Gradio interface
iface = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(type="filepath", label="Record or Upload Audio"),
    outputs="text"
)

# Launch the interface
iface.launch()