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开发与工程 · SKILL.md

text-to-speech

text-to-speech

【开发与工程】Use PaddleSpeech TTS acoustic models, vocoders, ONNX/static inference, multilingual options, and training recipe guidance safely.

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技能说明

GitHub

name: text-to-speech description: "Use PaddleSpeech TTS acoustic models, vocoders, ONNX/static inference, multilingual options, and training recipe guidance safely." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Text-to-Speech

Use this sub-skill for paddlespeech tts, TTSExecutor, acoustic/vocoder pairing, multi-speaker and multilingual options, ONNX/static choices, TTS training or synthesis recipe planning, voice cloning/SVS orientation, and TTS-specific troubleshooting.

Common Routes

  • Simple synthesis: read references/cli-and-api.md, then run paddlespeech tts --input ... --output output.wav after approving model downloads.
  • Choose AM/VOC/lang: read references/model-combinations-and-training.md before mixing acoustic models, vocoders, --lang, and --spk_id.
  • Batch Chinese synthesis: use scripts/build_tts_job.py for whitespace-free text job files; use direct quoted --input for English/spaced text.
  • ONNX or streaming TTS: use this sub-skill for model pairing, then route to ../deployment-serving/SKILL.md for server config and streaming protocols.
  • Training/fine-tuning recipes: read references/model-combinations-and-training.md; ask before dataset downloads, GPU jobs, or staged recipe execution.
  • Text frontend, G2P, TN, MFA: route to ../text-processing/SKILL.md when the task is text preparation rather than synthesis itself.

Safe Workflow

paddlespeech tts --input "你好,欢迎使用百度飞桨深度学习框架!" --output output.wav
paddlespeech tts --am fastspeech2_ljspeech --voc hifigan_ljspeech --lang en --input "Life was like a box of chocolates." --output en.wav
paddlespeech tts --am fastspeech2_aishell3 --voc hifigan_aishell3 --lang zh --spk_id 0 --input "你好" --output spk0.wav

Before running, confirm:

  1. The AM/VOC/lang combination exists.
  2. A pretrained run may download both AM and vocoder archives.
  3. The output extension is a writable .wav path.
  4. CPU can work but may be slow; GPU requires a matching PaddlePaddle GPU runtime.

References and Helper

  • references/cli-and-api.md covers TTS CLI options, Python executor, ONNX flags, and output behavior.
  • references/model-combinations-and-training.md maps acoustic/vocoder choices, language/multispeaker constraints, and recipe structure.
  • references/troubleshooting.md covers model pairing, frontend, dictionary/stat, ONNX, output, and batch parsing errors.
  • scripts/build_tts_job.py builds safe .job files for text without whitespace.

Do Not Do by Default

  • Do not run full TTS/vocoder training recipes, voice cloning, VC, SVS, VITS, or JETS recipes without approval.
  • Do not claim ONNX/Paddle Lite/Android/C++ deployment is verified from a dynamic Python synthesis check.
  • Do not use .job for English text with spaces unless you have verified the target parser accepts it; direct --input is safer.
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