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| import subprocess | |
| import streamlit as st | |
| import speech_recognition as sr | |
| from streaming_stt_nemo import Model | |
| if "sv_load_flash_attention" not in st.session_state: | |
| subprocess.run( | |
| "pip install flash-attn --no-build-isolation", | |
| env={"FLASH_ATTENTION_SKIP_CUDA_BUILD": "TRUE"}, | |
| shell=True, | |
| ) | |
| st.session_state.sv_load_flash_attention = True | |
| def main(): | |
| st.title("Speech to Text Converter") | |
| # Create a recognizer object | |
| r = sr.Recognizer() | |
| # Create a microphone object | |
| mic = sr.Microphone() | |
| # Continuously listen for audio input | |
| with mic as source: | |
| st.write("Listening...") | |
| while True: | |
| try: | |
| # Adjust the ambient noise threshold for better results | |
| r.adjust_for_ambient_noise(source) | |
| # Listen for audio input | |
| audio = r.listen(source) | |
| # Convert audio to text | |
| default_lang = "en" | |
| engines = { | |
| default_lang: Model(default_lang) | |
| } | |
| model = engines[default_lang] | |
| text = model.stt_file(audio)[0] | |
| # Display the converted text | |
| st.write("You said:", text) | |
| except sr.UnknownValueError: | |
| pass | |
| if __name__ == "__main__": | |
| main() |