| import asyncio |
| import logging |
| import socket |
| import time |
|
|
| import numpy as np |
| import pyaudio |
|
|
|
|
| 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)) |
|
|
