import streamlit as st import time from whisper_processor import process_audio def process_audio_streamlit(audio_file, model_name, lang): start_time = time.time() result = process_audio(audio_file, model_name=model_name, lang=lang) end_time = time.time() elapsed_time = end_time - start_time st.write("Time taken:", elapsed_time, "seconds") return result st.title("Audio Transcription") # Upload audio file uploaded_file = st.file_uploader("Choose an audio file") # Select model and language model_name = st.selectbox("Select model", ["tiny", "base", "small", "medium", "large"]) lang = st.selectbox("Select language", ["en", "hi", "fr", "de", "es", "it", "pt", "ru", "zh", "ja", "ko", "ar", "tr"]) if uploaded_file is not None: # Save the uploaded file to a temporary location with open("temp.wav", "wb") as f: f.write(uploaded_file.read()) # Process the audio file result = process_audio_streamlit("temp.wav", model_name, lang) # Display the transcription result st.write("Transcription:") st.text_area("", value=result, height=300)