| import socket | |
| import asyncio | |
| import pyaudio | |
| import numpy as np | |
| import logging | |
| import time | |
| logging.basicConfig(level=logging.INFO) | |
| logger = logging.getLogger(__name__) | |
| async def listen_to_F5TTS(text, server_ip="localhost", server_port=9998): | |
| client_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | |
| await asyncio.get_event_loop().run_in_executor(None, client_socket.connect, (server_ip, int(server_port))) | |
| start_time = time.time() | |
| first_chunk_time = None | |
| async def play_audio_stream(): | |
| nonlocal first_chunk_time | |
| p = pyaudio.PyAudio() | |
| stream = p.open(format=pyaudio.paFloat32, channels=1, rate=24000, output=True, frames_per_buffer=2048) | |
| try: | |
| while True: | |
| data = await asyncio.get_event_loop().run_in_executor(None, client_socket.recv, 8192) | |
| if not data: | |
| break | |
| if data == b"END": | |
| logger.info("End of audio received.") | |
| break | |
| audio_array = np.frombuffer(data, dtype=np.float32) | |
| stream.write(audio_array.tobytes()) | |
| if first_chunk_time is None: | |
| first_chunk_time = time.time() | |
| finally: | |
| stream.stop_stream() | |
| stream.close() | |
| p.terminate() | |
| logger.info(f"Total time taken: {time.time() - start_time:.4f} seconds") | |
| try: | |
| data_to_send = f"{text}".encode("utf-8") | |
| await asyncio.get_event_loop().run_in_executor(None, client_socket.sendall, data_to_send) | |
| await play_audio_stream() | |
| except Exception as e: | |
| logger.error(f"Error in listen_to_F5TTS: {e}") | |
| finally: | |
| client_socket.close() | |
| if __name__ == "__main__": | |
| text_to_send = "As a Reader assistant, I'm familiar with new technology. which are key to its improved performance in terms of both training speed and inference efficiency. Let's break down the components" | |
| asyncio.run(listen_to_F5TTS(text_to_send)) | |