d7fc0236bc
Specification change. Two different rules, and they need different
mechanisms.
Narrator: accent = translation language. Its reference was generated by
VoiceDesign from a description that hardcoded '{accent} English', baking an
American-English timbre into the WAV; cloning that into German gives German
phonology from an American voice. Ten per-language references now exist
(narrator_EN.wav ... narrator_ZH.wav), each designed from the narrator's
timbre plus 'Speaking {language} as a native {language} speaker'.
Characters: keep the accent on the speaker page. Their accents were already
encoded in their existing refs - what destroyed them was the language
parameter forced onto every utterance, which made every voice adopt the
target language's prosody. That is why Deal Hunter came out French-native.
Phonology and accent are now separate controls: language carries phonology,
an explicit voice_description carries accent character. Deal Hunter gets
'with a strong Australian accent' in every language.
Measured A/B, French line from Deal Hunter: with and without the Australian
instruction the waveforms differ by 152% of signal amplitude and duration
moves 4.24s -> 4.08s, so the instruction is reaching the model. Whether it is
convincingly Australian is an ear test, not something measurable here.
Re-rendered all 120 clips under the new spec, 0 failures. The previous
render is kept in Lang_test_preSpec for A/B. 24 speakers carry a non-default
accent; the narrator is deliberately excluded from that set.
Suite: 721 passed, 8 pre-existing.
UmbraAudio
Quality-first multi-pass audiobook generation from English manuscripts.
Features
- 5-pass pipeline: Analysis → Voice Design → Mapping → Test → Generate
- Multi-engine TTS: Chatterbox (primary), Qwen3-TTS (secondary)
- LLM-enhanced: BookNLP for NLP, LLM for profiling/emotion/pronunciation
- Web review: FastAPI + HTMX at checkpoints for human approval
Quick Start
python -m umbraaudio.cli init <manuscript.epub> --name 'My Book'
python -m umbraaudio.cli analyze
python -m umbraaudio.cli voices
python -m umbraaudio.cli review
Requirements
- Python 3.11+
- NVIDIA GPU with CUDA support (RTX 3060 or better recommended)
- ffmpeg
Development
pip install -e ".[dev]"
ruff check umbraaudio/
pytest tests/ -v
Commit cadence: commit at least once every Sunday. Never leave a week (let alone a month) of work uncommitted — a single accidental
git checkouton 2026-09-20 wiped out a month of changes toumbraaudio/web/routes.py. SeeAGENTS.md→ Commit Cadence.
scripts/commit_check.sh enforces the nudge: it exits non-zero once the tree has been dirty
longer than a week. The LaunchAgent com.umbraaudio.commitcheck runs it every Sunday at
18:00 and posts a macOS notification when there is uncommitted work.
scripts/commit_check.sh # warn if dirty > 7 days
scripts/commit_check.sh --days 3 # tighter threshold
scripts/commit_check.sh --any # warn on any uncommitted change
Rebuilding from source
The repo tracks source only; large runtime data is reconstructed as needed.
-
Models: weights are not committed (see
.gitignore). Download them:bash scripts/download_models.sh # ~9 GB, targets ./models -
Qwen3-TTS is a git submodule pinned to upstream commit
022e286:git submodule update --init --recursiveThe
tts_server/web-demo backend includes a local UI customization toqwen_tts/cli/demo.py. It is preserved as a patch — reapply it after checking out the submodule:cd Qwen3-TTS && git apply ../scripts/qwen3_tts_demo_umbra_patch.patch -
Environment: copy/keep
.env(contains secrets) and setUMBRA_TTS__*model paths undermodels/.
Book projects (e.g. DealHunterShip_...) are committed separately under their
own project directories and are not part of this program repository.