1. play auto cuda stream.py

from TTS.api import TTS
import numpy as np
import simpleaudio as sa
import torch

# Check if GPU is available
if torch.cuda.is_available():
    device = "cuda"
else:
    device = "cpu"

# Initialize the TTS object
tts = TTS(model_name="tts_models/multilingual/multi-dataset/xtts_v2", progress_bar=True)
tts.to(device)  # Use GPU if available

# Define a function to simulate streaming
def stream_tts(text, speaker="Ana Florence", language="en", chunk_size=20):
    # Split the text into smaller chunks
    words = text.split()
    chunks = [" ".join(words[i:i + chunk_size]) for i in range(0, len(words), chunk_size)]

    # Generate and play each chunk
    for chunk in chunks:
        print(f"Processing chunk: {chunk}")
        audio = tts.tts(
            text=chunk,
            speaker=speaker,
            language=language
        )

        # Convert the audio to a playable format
        audio_data = np.array(audio, dtype=np.float32)
        audio_data = (audio_data * 32767).astype(np.int16)  # Convert to 16-bit PCM
        play_obj = sa.play_buffer(audio_data, 1, 2, tts.synthesizer.output_sample_rate)
        play_obj.wait_done()  # Wait for the current chunk to finish playing

# Continuous loop for text input
print("Enter text to generate speech. Type 'exit' to quit.")
while True:
    # Get user input
    text = input("Enter text: ")

    # Exit the loop if the user types 'exit'
    if text.lower() == "exit":
        print("Exiting...")
        break

    # Stream the TTS
    print("Streaming speech...")
    stream_tts(text, speaker="Ana Florence", language="en")
    print("Streaming finished.")