最新开源tts，支持时时对话，延迟低于25ms，多规则适配多场景

cd Orpheus-TTS && pip install orpheus-speech # uses vllm under the hood for fast inference

pip install vllm==0.7.3

pip install orpheus-speech

from orpheus_tts import OrpheusModelimport waveimport time
model = OrpheusModel(model_name ="canopylabs/orpheus-tts-0.1-finetune-prod")prompt = '''Man, the way social media has, um, completely changed how we interact is just wild, right? Like, we're all connected 24/7 but somehow people feel more alone than ever. And don't even get me started on how it's messing with kids' self-esteem and mental health and whatnot.'''
start_time = time.monotonic()syn_tokens = model.generate_speech(   prompt=prompt,   voice="tara",   )
with wave.open("output.wav", "wb") as wf:   wf.setnchannels(1)   wf.setsampwidth(2)   wf.setframerate(24000)
   total_frames = 0   chunk_counter = 0   for audio_chunk in syn_tokens: # output streaming      chunk_counter += 1      frame_count = len(audio_chunk) // (wf.getsampwidth() * wf.getnchannels())      total_frames += frame_count      wf.writeframes(audio_chunk)   duration = total_frames / wf.getframerate()
   end_time = time.monotonic()   print(f"It took {end_time - start_time} seconds to generate {duration:.2f} seconds of audio")