ComfyUI-IF_AI_ParlerTTSNode

ComfyUI-IF_AI_ParlerTTSNode
★ 17

文本转语音情感语音合成零样本控制ComfyUI节点
将文本转为含情绪与抑扬顿挫的语音,支持通过提示词零样本控制声线与语气,便于在ComfyUI中集成语音合成。
💡 在ComfyUI内用文本提示生成带情感的语音
🍴 5 Forks💻 Python🔄 2025-03-14
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📄 README

IF_ParlerTTSNode: Comfy Node for Parler TTS

This node provides access to the high-quality Parler TTS with promptable descriptions within ComfyUI. It is part of the IF_AI_tools collection.

Installation

Prerequisites:

  • Python environment: You need a Python environment with pip. You can use virtual environments like venv or conda environments.
  • ComfyUI: Ensure you have ComfyUI installed and set up.
  • Installation Steps:

  • Activate your Python environment.
  • Install Parler TTS:
  • Linux/macOS:
  • “`bash

    pip install git+https://github.com/huggingface/parler-tts.git

    “`

  • Windows (Portable Embedded Python):
  • “`bash

    H:\ComfyUI_windows_portable\python_embeded\python.exe -m pip install git+https://github.com/huggingface/parler-tts.git

    “`

  • Install ffmpy (if necessary):
  • If you encounter issues with ffmpy, follow these instructions:
  • Download ffmpy from https://pypi.org/project/ffmpy/#files
  • Extract the downloaded code.
  • In the setup.py file, comment out line 4 (#from ffmpy import __version__).
  • Change the version string on line 8 to the actual version (e.g., version="0.3.0").
  • Open a terminal in the extracted ffmpy directory.
  • Run the following command, replacing with the path to your Python executable:
  • “`bash

    setup.py

    “`

  • Install importlib_resources (Windows Portable Embedded Python only):
  • “`bash

    H:\ComfyUI_windows_portable\python_embeded\python.exe -m pip install importlib_resources

    “`

    Usage

  • Once installed, the Parler TTS node should be available within ComfyUI.
  • You can use it to generate speech audio from text prompts, including descriptive details for controlling the speech style and characteristics.
  • Additional Notes

  • Refer to the Parler TTS documentation and examples for more information on using the model effectively.
  • * T