Commit Graph

5 Commits

Author SHA1 Message Date
Denis Defolie 1c036658bc Add regle_pluriel_nom and regle_accord_determinant (CE1)
Extends explicitly beyond the §15 prototype scope (3 missions, one
rule) that prompt-lancement.md says not to exceed without flagging
it — confirmed with the user before implementing (decisions.md,
point 25).

Adds the two remaining CE1 rules for the "accords dans le groupe
nominal" chapter listed in prompt-lancement.md, each with the same
minimum content volume already established for regle_accord_adjectif
(8 multiple-choice, 4 sentence corrections, 3 dictées across the 3
difficulty levels) and 3 missions (one per exercise type, matching
the existing pattern), bringing the map to 9 locations.

world_map.gd is purely data-driven already, so no code change was
needed to support more locations — only its stale "trois lieux"
header comment, corrected. Dictation audio generated with the Piper
voice (make generate-dictation-audio).

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-10-11 21:36:04 +02:00
Denis Defolie 26d588f1bc Add 2 dictées for the accords-du-groupe-nominal chapter
Only 1 existed, below the prompt-lancement.md minimum of 3 per
chapter. Adds difficulty 2 (feminine singular) and difficulty 3
(feminine plural, noun and adjective separated by a complement,
mirroring points 18/23). Audio generated with the Piper voice
(make generate-dictation-audio), credited in assets/CREDITS.md.

With this, regle_accord_adjectif now meets prompt-lancement.md's
minimum content volume: 8 multiple-choice, 4 sentence corrections,
3 dictées.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-10-11 21:15:26 +02:00
Denis Defolie b0dcedb402 Replace eSpeak NG with Piper neural voice for dictation audio
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>
2026-10-11 19:07:40 +02:00
Denis Defolie 73440ba226 Generate provisional dictation audio so dictée missions can be played
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>
2026-10-11 18:40:11 +02:00
Denis Defolie 493a8617d7 Add the playable scene loop: boot through mission to reward
Wires every autoload up to a real UI: boot -> profile select/create
-> world map (three mission markers, positioned from data, not
hardcoded pixels) -> mission intro (narrative from data/missions/,
a new data type with its own schema) -> rule panel -> exercise host
-> one of the three exercise type scenes -> feedback panel -> reward
screen -> back to the map.

exercise_host is the only piece with real orchestration logic: picks
exercises via ExerciseEngine (now fully implemented, validating at
load like make validate-data does), validates answers through the
pure AnswerValidator/DictationAnalyzer, escalates aid over 3 attempts
via AttemptFlow, feeds DifficultyManager so adaptive difficulty is
actually wired in rather than dead code, and records every attempt
through ProgressManager. Every exercise-type scene (multiple_choice,
sentence_correction, dictation) only emits its answer by signal, per
the architecture invariant.

All child-facing text now comes from data/localization/fr.json via
UIText, not hardcoded in scripts or scenes. Getting that right
required extending SchemaValidator to support "additionalProperties"
as a schema (dynamic keys), which also closed a real gap: save.skills
was previously unvalidated against SkillState's actual shape.

16 new headless tests, including two integration tests that instance
exercise_host.tscn directly and drive it by emitting child-scene
signals, stopping short of the final scene transition (which would
tear down the test runner's own tree). Everything that needs a
screen -- layout at different sizes, touch, virtual keyboard, actual
audio playback (no .ogg files exist yet) -- is listed in the new
docs/testing/manual-checklist.md instead of claimed as verified.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-10-11 17:37:37 +02:00