Each emotion can now be tuned independently. parse_segments resolves the four
controls per segment from a base (공통) dict plus an optional per-emotion
override; a missing override key inherits base. By default there are no
overrides, so every emotion delivers with the base values (모든 감정 = 기본값).
- emotion.py: Segment now carries all 4 controls + the canonical emotion name;
parse_segments(text, base, overrides). Adds EMOTION_LABELS/EMOTIONS for the UI.
- melo.py: MeloTTS.emotion_overrides store; synth resolves per-segment controls
and sends them per segment.
- melo_worker.py: _render applies each segment's own word_gap/sentence_gap/pitch
(previously reply-global).
- dashboard.py: emotion dropdown in the TTS panel; GET returns base + overrides
+ emotion list; POST {emotion,...} stores an override (or {reset:true} clears
it); base is set when emotion is omitted/"base".
Verified: an override on one emotion slows only that emotion (happy@0.7=5.66s vs
base 3.02s; sad unchanged at 3.06s); dashboard store/reset/base all work; 34
tests pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
User reported the emotion samples sounded the same and the speed change wasn't
noticeable. Two changes:
- Add a "base" (기본/neutral) emotion at speed 1.0x so the plain base voice can
be selected explicitly via a [기본] tag and auditioned against the others.
- Bump the WSAI_TTS_SPEED default 1.15 -> 1.5 for a clearly faster base voice.
Emotion multipliers scale off base, so every emotion speeds up together.
Also extends gen_emotion_samples.py to emit one wav per emotion (incl. 기본)
plus a stitched all-in-one, so each emotion can be delivered as a separate clip.
Verified: 29 tests pass; match_emotion('기본') == 'base'; per-emotion synthesis
at base 1.5 produces distinct clip durations (base 4.9s vs happy 3.3s).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The emotional TTS path applied a librosa post-hoc pitch_shift (±1–3 semitones)
on top of a 1.3x-fast Melo base, producing a robotic "monster" delivery. Zero
out the pitch column for every emotion so pitch_shift is never invoked (the
worker's _pitch_shift already no-ops on 0.0), and drop the default synthesis
speed to 1.0. Emotion is now conveyed by speed alone — natural, artefact-free.
The pitch column is retained so a proper pitch method can be re-enabled later.
Verified: 29 tests pass; real 2-emotion synthesis on CUDA yields a clean wav
with pitch=0.0 on all segments.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Emotion tags now steer delivery rather than being read aloud. parse_segments()
splits a reply on [감정] tags: a recognised emotion word switches the pitch and
speed of the text that follows (and is dropped), while a non-emotion bracket
(e.g. [1번]) keeps its inner words as spoken content. Emotions can change
mid-reply, so a single turn is synthesised as several pitch-shifted segments and
concatenated in the melo worker (librosa pitch_shift, warmed at startup).
The emotion vocabulary is grounded in Azure Neural TTS speaking styles plus
Ekman's basic emotions, with Korean synonyms. The brain persona is updated to
emit inline tags from that set.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
