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| import streamlit as st | |
| import whisper | |
| from tempfile import NamedTemporaryFile | |
| import ffmpeg | |
| st.title("Whisper App") | |
| # upload audio file with streamlit | |
| audio_file = st.file_uploader("Upload Meeting Audio", type=["m4a", "mp3", "wav"]) | |
| st.text("Whisper Model Loaded") | |
| def load_whisper_model(): | |
| return model | |
| def convert_m4a_to_mp3(input_path, output_path): | |
| audio = AudioSegment.from_file(input_path, format="m4a") | |
| audio.export(output_path, format="mp3") | |
| if st.sidebar.button("Transcribe Audio"): | |
| if audio_file is not None: | |
| with NamedTemporaryFile(suffix="mp3") as temp: | |
| temp.write(audio_file.getvalue()) | |
| temp.seek(0) | |
| model = whisper.load_model("base") | |
| temp_mp3_path = temp.name | |
| convert_m4a_to_mp3(audio_file, temp_mp3_path) | |
| result = model.transcribe(temp_mp3_path) | |
| st.write(result["text"]) | |
| st.sidebar.header("Play Original Audio File") | |
| st.sidebar.audio(audio_file) |