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app.py

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+import torch
+from TTS.api import TTS
+import streamlit as st
+import time
+
+def settings ():
+    global device, tts, speaker_wav
+    # Get device
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+    tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
+    speaker_wav ="sounds/alp.mp3"
+
+
+
+st.header("Bas Konuş")
+st.text_input("Konuşmak istediğiniz metni girin")
+speaker=st.button("Konuş")
+
+text = """Data bank'a hoşgeldiniz. Ben asistanınız esra, size nasıl yardımcı olabilirim?"""
+
+
+if speaker:
+    start_time = time.time()  # Start the timer
+
+    settings()
+    output_path = tts.tts_to_file(text=text, speaker_wav=speaker_wav ,language="tr")
+
+    end_time = time.time()  # End the timer
+
+    execution_time = end_time - start_time  # Calculate the time taken
+
+    st.write(f"Execution time: {execution_time} seconds")  # Display the time taken
+
+    st.audio(output_path, format="audio/mp3")
+
+
+

requirements.txt

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+streamlit
+TTS
+pytorch