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El SDK CI - dev / build-and-test (pull_request) Successful in 6m28s
speech.el: formant/glottal integer DSP synthesis + voice-analyze-by-
imitation. voice-profile.el / voice-ingest.el: voice-profile plumbing.
accent.el: British-RP as an ingested transform-geometry (explicitly marked
provisional/citation-pending by its own comments). organ-read.el:
engram read-through for the speech organ. Includes demo/test drivers and
non-personal reference data (British-RP phonetics/lexicon derived data,
a public-domain LibriVox RP reference recording).
Deliberately excludes elp/data/live/ (raw recorded voice + face-photo
samples of the repo owner) and the will-*.{json,psv} derived voiceprint
files — personal biometric data that shouldn't be committed to a shared
repo without an explicit decision from the owner. Also excludes this
worktree's elp/src/surface-profile.el, which diverges from the copy in
other worktrees (agent-aaf04b0a9714c4070, main) — needs manual
reconciliation before landing, left out here to avoid silently picking a
version.
49 lines
3.0 KiB
EmacsLisp
49 lines
3.0 KiB
EmacsLisp
// speech-organ-demo.el - PROOF: the render now reads its phoneme + accent
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// GEOMETRY from the ingest ORGAN's saved engram files (engram_load +
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// engram_scan_nodes_json + cache), not a same-run hand-load. The British accent
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// is still a composed transform-geometry (voice (+) accent, separable). Numbers
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// come from the organ manifold; the .psv supplies only categorical vowel-class.
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fn main() {
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let outdir: String = "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-acc02900ef4ade35e/elp/tests/examples/out/"
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// engram-independent caches from source (survive engram_load replacement)
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let vset: [String] = organ_vset("elp/data/phonetics.psv")
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let lmap: [String] = organ_lex("elp/data/lexicon.psv")
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// ORGAN read: phonetics FIRST (cache), THEN accent (engram_load replaces store)
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let pmap: [String] = organ_pmap("elp/data/phonetics-formants.engram.json")
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let amap: [String] = organ_amap("elp/data/british-accent.engram.json")
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println("[organ] phon_syms=" + int_to_str(native_list_len(pmap) / 2) + " accent_syms=" + int_to_str(native_list_len(amap) / 2) + " vowels=" + int_to_str(native_list_len(vset)) + " words=" + int_to_str(native_list_len(lmap) / 2))
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// prove the numbers came from the organ node content
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let g: [Int] = phon_geo(pmap, "AA")
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println("[organ-read] phoneme AA f1=" + int_to_str(native_list_get(g, 0)) + " f2=" + int_to_str(native_list_get(g, 1)) + " f3=" + int_to_str(native_list_get(g, 2)) + " (P&B1952 MEASURED)")
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let ov: [Int] = accent_formants(amap, "AA")
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if native_list_len(ov) >= 3 {
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println("[organ-read] accent AA(LOT) f1=" + int_to_str(native_list_get(ov, 0)) + " f2=" + int_to_str(native_list_get(ov, 1)) + " (DERIVED RP, PROVISIONAL)")
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}
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println("[organ-read] non_rhotic=" + int_to_str(is_nonrhotic(amap)))
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let neuron: [String] = voice_neuron()
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let noacc: [String] = native_list_empty()
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// Sentence 1: "I am Neuron." from meaning; GA vs RP = separable toggle
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let t1: String = sem_realize(sem_frame("describe", "I", "Neuron", ""))
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let c1: [String] = text_phonemes(lmap, t1)
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println("[s1] " + t1 + " :: " + list_join(c1, " "))
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let ga: [Int] = synth_codes_accent(c1, neuron, pmap, noacc, vset)
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let okga: Bool = write_wav(ga, 16000, outdir + "ga-neuron-organ.wav")
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let br1: [Int] = synth_codes_accent(c1, neuron, pmap, amap, vset)
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let okb1: Bool = write_wav(br1, 16000, outdir + "british-neuron-organ.wav")
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// Sentence 2: non-rhoticity showcase
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let t2: String = sem_realize(sem_frame("describe", "I", "here", ""))
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let c2: [String] = text_phonemes(lmap, t2)
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let c2rp: [String] = apply_rhoticity(c2, vset)
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println("[s2] " + t2 + " :: GA=" + list_join(c2, " ") + " RP=" + list_join(c2rp, " "))
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let br2: [Int] = synth_codes_accent(c2, neuron, pmap, amap, vset)
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let okb2: Bool = write_wav(br2, 16000, outdir + "british-2-organ.wav")
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println("[done] ga-organ=" + bool_to_str(okga) + " british-organ=" + bool_to_str(okb1) + " british-2-organ=" + bool_to_str(okb2))
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}
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