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from TTS.api import TTS
import numpy as np
import simpleaudio as sa
import torch
import threading
import queue
# 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
# Queue to hold audio chunks for playback
audio_queue = queue.Queue()
# Function to process text and generate audio chunks
def tts_worker(text, speaker="Ana Florence", language="en", chunk_size=10):
words = text.split()
chunks = [" ".join(words[i:i + chunk_size]) for i in range(0, len(words), chunk_size)]
for chunk in chunks:
print(f"Processing chunk: {chunk}")
audio = tts.tts(
text=chunk,
speaker=speaker,
language=language
)
audio_data = np.array(audio, dtype=np.float32)
audio_data = (audio_data * 32767).astype(np.int16) # Convert to 16-bit PCM
audio_queue.put(audio_data) # Add the audio chunk to the queue
audio_queue.put(None) # Signal the end of processing
# Function to play audio chunks
def audio_worker():
while True:
audio_data = audio_queue.get() # Get the next audio chunk
if audio_data is None: # End of processing
break
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
# Start the TTS worker thread
tts_thread = threading.Thread(target=tts_worker, args=(text, "Ana Florence", "en"))
tts_thread.start()
# Start the audio worker thread
audio_thread = threading.Thread(target=audio_worker)
audio_thread.start()
# Wait for both threads to finish
tts_thread.join()
audio_thread.join()
print("Streaming finished.") |