OuteTTS 模型

OuteTTS 发布新的版本，0.2 版本使用了 Qwen-2.5-0.5B 作为基础模型进行训练，OuteTTS 使用了 WavTokenizer，并将文字 Token 与 语音 Token 做了一对一的对应。TTS 也支持自定义读音。

OuteTTS 文字转音频

#安装依赖
pip install outetts

import outetts

# Configure the model
model_config = outetts.HFModelConfig_v1(
    model_path="OuteAI/OuteTTS-0.2-500M",
    language="zh",  # Supported languages in v0.2: en, zh, ja, ko
)

# Initialize the interface
interface = outetts.InterfaceHF(model_version="0.2", cfg=model_config)

# 以下代码为自定义读音代码，更改对应路径即可
# Optional: Create a speaker profile (use a 10-15 second audio clip)
# speaker = interface.create_speaker(
#     audio_path="path/to/audio/file",
#     transcript="Transcription of the audio file."
# )

# Optional: Save and load speaker profiles
# interface.save_speaker(speaker, "speaker.json")
# speaker = interface.load_speaker("speaker.json")

# Optional: Load speaker from default presets
interface.print_default_speakers()
speaker = interface.load_default_speaker(name="female_1")

output = interface.generate(
    text="""黄花又名忘忧草，既能食用，也能药用。""",
    # Lower temperature values may result in a more stable tone,
    # while higher values can introduce varied and expressive speech
    temperature=0.1,
    repetition_penalty=1.1,
    max_length=4096,

    # Optional: Use a speaker profile for consistent voice characteristics
    # Without a speaker profile, the model will generate a voice with random characteristics
    speaker=speaker,
)

# Save the synthesized speech to a file
output.save("output.wav")

# Optional: Play the synthesized speech
# output.play()

总结

OuteTTS 中文效果不如 F5-TTS，英文效果还是不错的，读数字也不是很好，需要先转换一下，OuteTTS 最大长度 4096， 更长的文字需要自己进行切分。