Manual test reported the eSpeak NG dictation voice as unintelligible.
Formant synthesis is inherently mechanical; slowing it down doesn't
fix that. Switched tools/generate_dictation_audio.py to piper-tts
(fr_FR-siwis-medium neural voice, MIT/CC-BY 4.0, attribution in
assets/CREDITS.md). The voice model (~60MB) downloads once on demand
into the untracked .cache/piper-voices/, never at game runtime.
Adds piper-tts to tools/setup.sh's venv and a pyrightconfig.json
pointing pyright at .venv, needed once tools/ imports a real
third-party package (`make lint` was silently checking against the
wrong interpreter before).
Regenerated ce1_accord_adjectif_dictee_01.ogg with the new voice.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Manual testing confirmed the "La clairière de l'écho" dictée mission
was unplayable: no audio file existed yet (decisions.md point 8), so
there was nothing to listen to before transcribing the sentence.
Adds tools/generate_dictation_audio.py (offline eSpeak NG synthesis +
ffmpeg encoding to Ogg Vorbis, exposed as `make
generate-dictation-audio`) and uses it to generate
ce1_accord_adjectif_dictee_01.ogg. A new headless test
(tests/data/test_dictation_audio.gd) guards against future dictées
being added without regenerating their audio.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Introduces a generic JSON-Schema-subset validator in GDScript
(scripts/data/schema_validator.gd) used both by `make validate-data`
and, later, by ExerciseEngine at load time, plus semantic_checks.gd
for cross-field constraints a schema can't express (answer index
bounds, at least one faulty token in sentence correction, word count
matching between a dictation's target_text and its annotations).
Schemas cover rule, exercise (dispatched per type: multiple_choice,
sentence_correction), dictation, curriculum, and save (save.schema.json
is not yet wired into validate-data; saves live in user://, handled
at the Profiles/Saves step).
First draft content for the CE1 "accord_adjectif" rule (one rule, two
multiple-choice exercises, one sentence correction, one dictation,
one curriculum entry) exercises the full pipeline end to end and
seeds docs/review/content-review.md, regenerated by the new
tools/generate_content_review.py (`make content-review`).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Denis Defolie