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| pip install recognize_speech | |
| import streamlit as st | |
| import recognize_speech as sr | |
| def recognize_speech(duration): | |
| # initialize the recognizer | |
| r = sr.Recognizer() | |
| st.info("Lütfen konuşun") | |
| with sr.Microphone() as source: | |
| st.warning("Kaydediliyor...") | |
| # read the audio data from the default microphone | |
| audio_data = r.record(source, duration=duration) | |
| st.success("Kayıt Tamamlandı!") | |
| st.subheader("Tanınan Metin:") | |
| # convert speech to text with Turkish language support | |
| try: | |
| text = r.recognize_google(audio_data, language="tr-TR") | |
| st.write(text) | |
| # Save the recognized text to a text file | |
| save_to_file(text, "recognized_text.txt") | |
| st.success("Tanınan metin başarıyla bir dosyaya kaydedildi: recognized_text.txt") | |
| except sr.UnknownValueError: | |
| st.error("Konuşma Anlaşılamadı") | |
| except sr.RequestError as e: | |
| st.error(f"Hata Oluştu: {e}") | |
| def save_to_file(text, file_path): | |
| with open(file_path, "w", encoding="utf-8") as file: | |
| file.write(text) | |
| def main(): | |
| st.title("Canlı Kayıdı Metine Dönüştürme") | |
| duration = st.slider("Kayıt Süresi (saniye)", min_value=1, max_value=60, value=3, step=1) | |
| if st.button("Başla"): | |
| recognize_speech(duration) | |
| if __name__ == "__main__": | |
| main() | |