name: training-config-data
description: "Prepare Coqui TTS datasets, Coqpit configs, tokenizer or
phonemizer settings, and safe training or fine-tuning plans without launching
expensive training by default."
disable-model-invocation: true
metadata:
disco-role: operating
license: MPL 2.0
Training, Configuration, and Data Sub-Skill
Use this sub-skill when a task asks how to prepare a Coqui TTS dataset, validate a TTS model config, adapt a training or fine-tuning workflow, inspect tokenizer/phonemizer coverage, or compute speaker embeddings/d-vectors safely.
Read order
- Start with references/configuration.md for Coqpit config hierarchy, model config registration, and the minimum fields to validate before training.
- Use references/data-formats.md for formatter schemas, LJSpeech/Common Voice/custom dataset layouts, and sample dictionaries returned by dataset loaders.
- Use references/training-workflows.md to turn a validated config into a training command template and to interpret Trainer flags.
- Use references/fine-tuning.md for released-checkpoint fine-tuning, XTTS GPT fine-tuning caveats, and safe override patterns.
- Use references/api-reference.md for compact API/CLI signatures and bundled helper contracts.
- Use references/troubleshooting.md for workflow-specific failures; use ../../references/troubleshooting.md for package install/import/runtime issues.
Safe bundled helpers
scripts/validate_tts_config.py: load a JSON/YAML config with Coqpit, check model registration, inspect dataset/audio paths, and optionally load dataset samples. It never initializes a model or starts training.scripts/find_unique_symbols.py: inspect unique graphemes or phonemes from configured datasets. Phoneme mode reports missing phonemizer/espeak dependencies clearly.scripts/compute_speaker_embeddings.py: a safe wrapper around speaker embedding generation. It requires explicit encoder model/config/dataset arguments and only computes embeddings when --run is passed.
Run helpers with --help first and keep outputs in a user-chosen working directory, not in the skill tree.
Boundaries and routing
- For vocoder training, audio statistics, resampling, silence trimming, spectrogram extraction, and vocoder-specific audio configuration, route to ../vocoder-and-audio-tools/SKILL.md.
- For inference from a trained checkpoint through Python APIs or the model zoo, route to ../inference-and-model-zoo/SKILL.md.
- For installed
tts or tts-server command syntax, route to ../server-and-cli/SKILL.md.
- For FreeVC source/target voice conversion workflows, route to ../voice-conversion/SKILL.md.
- Maintainer documentation-sync utilities are excluded: they mutate package documentation and are not runtime training/config/data operations.
Operating rules
- Do not run full training, fine-tuning, model downloads, or dataset downloads unless the user explicitly asks and accepts time, compute, disk, and network cost.
- Prefer config validation, formatter dry-runs, unique-symbol scans, and command construction as the default response.
- Treat Python
>=3.9,<3.12 as the supported package range.
- For phoneme workflows, expect optional language frontend/system dependencies such as
gruut, espeak, or espeak-ng.
- Keep vocoder and inference concerns routed rather than duplicating those workflows here.