app.py

import gradio as gr
from transformers import pipeline
from pydub import AudioSegment
import os

# Load a smaller Whisper model for faster transcription
model = pipeline("automatic-speech-recognition", model="openai/whisper-base")

def split_audio(filepath, chunk_length_ms=30000):
    """Split audio into chunks of `chunk_length_ms` milliseconds."""
    audio = AudioSegment.from_file(filepath)
    chunks = []
    for i in range(0, len(audio), chunk_length_ms):
        chunk = audio[i:i + chunk_length_ms]
        chunk_path = f"chunk_{i}.wav"
        chunk.export(chunk_path, format="wav")
        chunks.append(chunk_path)
    return chunks

def transcribe_audio(audio_file):
    # Split the audio into chunks
    chunks = split_audio(audio_file)
    
    # Transcribe each chunk and collect results
    transcriptions = []
    detected_language = None
    
    for chunk in chunks:
        # Enable language detection and transcription
        result = model(chunk, generate_kwargs={"task": "transcribe", "language": None})  # Let Whisper detect language
        transcriptions.append(result["text"])
        
        # Extract detected language from the result (if available)
        if "language" in result:
            detected_language = result["language"]
        
        os.remove(chunk)  # Clean up chunk files
    
    # Combine all transcriptions into one
    full_transcription = " ".join(transcriptions)
    
    # If no language was detected, set a default message
    if detected_language is None:
        detected_language = "unknown (language not detected)"
    
    # Return transcription and detected language
    return f"Detected Language: {detected_language}\n\nTranscription:\n{full_transcription}"

# Define the Gradio interface
iface = gr.Interface(
    fn=transcribe_audio,
    inputs=gr.Audio(type="filepath", label="Upload Audio File"),
    outputs=gr.Textbox(label="Transcription and Detected Language"),
    title="Audio Transcription with Automatic Language Detection",
    description="Upload an audio file, and the system will automatically detect the language and transcribe it."
)

# Launch the Gradio interface
iface.launch()