Weksa/examples/speech-training/tiny-panphon-v0.1/alveolar-ta.json
2026-05-21 10:21:48 +01:00

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{
"schema_version": "weksa.utterance_embedding_handoff.v0.1",
"packet_id": "tiny-panphon-v0.1/alveolar-ta",
"source_output_ref": "examples/speech-training/tiny-panphon-v0.1/README.md",
"speaker_agent_id": "neutral-human-baseline",
"text": {
"spoken_text": "ta",
"normalized_text": "ta",
"channel_note": "Pure IPA curriculum seed; semantic text embedding is intentionally zero."
},
"inputs": {
"speech_text_embedding": {
"model_id": "bge-m3:latest",
"dimensionality": 1024,
"values_ref": "vectors/zero-semantic-1024.json"
},
"panphon_sequence": {
"model_id": "panphon.v0.1.seed",
"source": "hand-authored seed phones for AquaSynth crawl-stage parity tests",
"ipa": "ta",
"feature_order": [
"syl",
"son",
"cons",
"cont",
"delrel",
"lat",
"nas",
"strid",
"voi",
"sg",
"cg",
"ant",
"cor",
"distr",
"lab",
"hi",
"lo",
"back",
"round",
"velaric",
"tense",
"long"
],
"frames": [
{
"index": 0,
"phone": "t",
"features": [
-1.0,
-1.0,
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0.0,
-1.0,
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0.0,
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],
"markers": {
"stress": 0.0,
"length": 0.0,
"tone": 0.0,
"boundary": 0.0,
"duration_ms": 95
}
},
{
"index": 1,
"phone": "a",
"features": [
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],
"markers": {
"stress": 1.0,
"length": 0.0,
"tone": 0.0,
"boundary": 1.0,
"duration_ms": 180
}
}
]
},
"prosody_emphasis_hints": {
"dimensionality": 32,
"labels": [
"mean_pitch_pressure",
"pitch_rise",
"pitch_fall",
"pitch_range",
"loudness_pressure",
"loudness_attack",
"loudness_release",
"speaking_rate",
"articulation_precision",
"pause_pressure",
"phrase_final_lengthening",
"stress_contrast",
"clippedness",
"breathiness",
"creak_pressure",
"smoothness",
"warmth",
"threat",
"urgency",
"hesitation",
"irony_dryness",
"tenderness",
"contempt",
"command_force",
"question_contour",
"exclamation_pressure",
"secrecy_low_projection",
"ritual_formality_pressure",
"playful_pressure",
"fatigue",
"emotional_containment",
"reserved"
],
"values": [
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0.0,
-0.15,
0.35,
0.0,
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0.2,
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0.25,
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]
},
"character_state_vector": {
"source": "epiphany.agent_utterance_state.v0 neutral baseline",
"schema_ref": "E:/Projects/EpiphanyAgent/schemas/agent-utterance-state-schema.md",
"dimensionality": 64,
"values_ref": "vectors/neutral-character-64.json"
}
},
"phonetic_realization_embedding": {
"owner": "AquaSynth",
"model_id": "aquasynth.panphon_sequence_encoder.v0.1",
"dimensionality": 256,
"status": "pending_aquasynth_training_or_encoding",
"values_ref": null
},
"utterance_embedding": {
"owner": "AquaSynth",
"model_id": "aquasynth.utterance_embedding_encoder.v0.1",
"version": null,
"training_set": "tiny-panphon-v0.1",
"dimensionality": 64,
"status": "pending_aquasynth_training_or_encoding",
"values_ref": null
},
"audit_projection": {
"semantic_preservation": "No lexical semantics; preserve the requested IPA sound shape.",
"emphasis": "Single syllable baseline stress where a vowel exists.",
"prosody": "Neutral, slow, precise, no expressive contour.",
"character_pressure": "Neutral speaker baseline.",
"delivery_shape": "voiceless alveolar stop into open vowel"
},
"training_refs": {
"positive_examples": [
{
"kind": "reference_synth_prompt",
"engine": "eSpeak NG or equivalent baseline speech oracle",
"text": "ta"
}
],
"negative_examples": []
},
"trace": {
"pipeline_receipts": [
{
"stage": "weksa_emit_tiny_panphon_handoff",
"decided_at_utc": "2026-05-20T00:00:00Z",
"latency_budget_ms": 10,
"observed_latency_ms": 0,
"confidence": 0.72
}
],
"notes": [
"This fixture is a crawl-stage training seed, not a full English lowering artifact.",
"The schema uses PanPhon's 22-feature basis; these seed values are hand-authored for the six seed phones until Weksa wires a canonical PanPhon dependency.",
"AquaSynth owns the learned 256-float phonetic realization embedding and 64-float utterance embedding."
],
"uncertainties": [
"Feature values should be regenerated from the canonical PanPhon library before broad phoneme coverage.",
"Durations are seed timing hints, not measured reference audio."
]
}
}