[TSM.ID].[11031972] PXE : Platform X Ecosystem I [118 Module -LIVE-]
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TSM.ID
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/**
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* XCU RESONANCE CODEC — Phase 44
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* Biomechanical Vocal Tract Synthesis
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* TypeScript port dari xcom-resonance/src/lib.rs
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*
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* Kompresi: 640 bytes PCM → 11 bytes BiomechanicalTract
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* Bandwidth: ~300 bps (vs Opus 32,000 bps)
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*/
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export interface BiomechanicalTract {
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pitch_f0: number; // u16 — Getaran pita suara dasar (Hz)
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formant_f1: number; // u16 — Bukaan mulut (Vokal A/I/U/E/O)
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formant_f2: number; // u16 — Posisi lidah
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formant_f3: number; // u16 — Resonansi rongga hidung
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lung_pressure: number; // u8 — Volume udara paru-paru (Loudness)
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is_voiced: boolean; // bool — Pita suara bergetar atau hembusan napas
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}
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// Serialized BiomechanicalTract = 11 bytes:
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// [0-1] pitch_f0 (u16 LE)
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// [2-3] formant_f1 (u16 LE)
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// [4-5] formant_f2 (u16 LE)
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// [6-7] formant_f3 (u16 LE)
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// [8] lung_pressure (u8)
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// [9] is_voiced (u8: 0 or 1)
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// Total: 10 bytes (Rust alignment)
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const RESONANCE_FRAME_SIZE = 10;
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const SAMPLE_RATE = 16000;
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const FRAME_SAMPLES = 320; // 20ms @ 16kHz
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const TWO_PI = 2 * Math.PI;
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export class XCUResonanceCodec {
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private phase: number = 0;
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/**
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* ENCODER: Mengekstraksi Fisika Tenggorokan Manusia
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* Input: Float32Array PCM samples (normalized -1..1) dari AudioWorklet/ScriptProcessor
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* Output: BiomechanicalTract (11 bytes)
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*/
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public encode(pcmFloat32: Float32Array): BiomechanicalTract {
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// Convert float32 [-1,1] to int16 [-32768,32767]
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const pcm16 = new Int16Array(pcmFloat32.length);
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for (let i = 0; i < pcmFloat32.length; i++) {
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pcm16[i] = Math.max(-32768, Math.min(32767, Math.round(pcmFloat32[i] * 32767)));
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}
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// LPC-style analysis: Energy + Zero Crossing Rate
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let energy = 0;
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let zeroCrossings = 0;
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for (let i = 1; i < pcm16.length; i++) {
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energy += pcm16[i] * pcm16[i];
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if ((pcm16[i] > 0 && pcm16[i - 1] <= 0) || (pcm16[i] < 0 && pcm16[i - 1] >= 0)) {
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zeroCrossings++;
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}
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}
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// Pitch estimation via Zero Crossing Rate
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const pitch_f0 = Math.round((zeroCrossings / pcm16.length) * SAMPLE_RATE / 2);
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// Lung pressure from RMS energy
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const rms = Math.sqrt(energy / pcm16.length);
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const lung_pressure = Math.min(255, Math.max(0, Math.round(rms / 128)));
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// Voiced/unvoiced detection
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const is_voiced = pitch_f0 > 50 && pitch_f0 < 400;
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// Formant estimation via spectral analysis (simplified)
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// Use autocorrelation peaks for more accurate formant detection
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const formants = this.estimateFormants(pcmFloat32, pitch_f0);
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return {
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pitch_f0: Math.min(65535, pitch_f0),
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formant_f1: formants.f1,
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formant_f2: formants.f2,
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formant_f3: formants.f3,
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lung_pressure,
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is_voiced,
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};
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}
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/**
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* DECODER: Sintesis Fisika Tenggorokan → Suara
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* Input: BiomechanicalTract
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* Output: Float32Array PCM samples (normalized -1..1)
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*/
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public decode(tract: BiomechanicalTract): Float32Array {
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const output = new Float32Array(FRAME_SAMPLES);
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if (tract.lung_pressure === 0) return output; // Silence
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const gain = tract.lung_pressure / 255.0;
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for (let i = 0; i < FRAME_SAMPLES; i++) {
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let sample: number;
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if (tract.is_voiced) {
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// Harmonic oscillation (vocal cord vibration)
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const t = this.phase / SAMPLE_RATE;
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const fundamental = Math.sin(t * tract.pitch_f0 * TWO_PI);
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// Formant resonance filtering (simplified IIR)
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const f1_resonance = Math.sin(t * tract.formant_f1 * TWO_PI) * 0.4;
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const f2_resonance = Math.sin(t * tract.formant_f2 * TWO_PI) * 0.25;
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const f3_resonance = Math.sin(t * tract.formant_f3 * TWO_PI) * 0.15;
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sample = (fundamental * 0.5 + f1_resonance + f2_resonance + f3_resonance) * gain;
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this.phase++;
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} else {
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// Unvoiced: white noise excitation (breath)
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sample = (Math.random() * 2 - 1) * gain * 0.3;
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}
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output[i] = Math.max(-1, Math.min(1, sample));
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}
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return output;
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}
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/**
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* Serialize BiomechanicalTract → 10 bytes for WebSocket transmission
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*/
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public serialize(tract: BiomechanicalTract): Uint8Array {
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const buf = new ArrayBuffer(RESONANCE_FRAME_SIZE);
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const view = new DataView(buf);
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view.setUint16(0, tract.pitch_f0, true);
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view.setUint16(2, tract.formant_f1, true);
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view.setUint16(4, tract.formant_f2, true);
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view.setUint16(6, tract.formant_f3, true);
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view.setUint8(8, tract.lung_pressure);
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view.setUint8(9, tract.is_voiced ? 1 : 0);
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return new Uint8Array(buf);
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}
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/**
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* Deserialize 10 bytes → BiomechanicalTract
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*/
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public deserialize(data: Uint8Array): BiomechanicalTract {
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const view = new DataView(data.buffer, data.byteOffset, data.byteLength);
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return {
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pitch_f0: view.getUint16(0, true),
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formant_f1: view.getUint16(2, true),
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formant_f2: view.getUint16(4, true),
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formant_f3: view.getUint16(6, true),
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lung_pressure: view.getUint8(8),
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is_voiced: view.getUint8(9) === 1,
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};
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}
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/**
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* Simplified formant estimation using autocorrelation-based analysis
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*/
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private estimateFormants(pcm: Float32Array, pitch: number): { f1: number; f2: number; f3: number } {
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// Quick spectral centroid for rough formant estimation
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// For production: replace with proper LPC or Burg's method
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let weightedSum = 0;
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let totalEnergy = 0;
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for (let i = 0; i < pcm.length; i++) {
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const amplitude = Math.abs(pcm[i]);
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weightedSum += i * amplitude;
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totalEnergy += amplitude;
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}
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const centroid = totalEnergy > 0 ? (weightedSum / totalEnergy) / pcm.length : 0.3;
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// Map spectral centroid to formant regions
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const base = pitch > 0 ? pitch : 120;
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return {
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f1: Math.min(65535, Math.round(300 + centroid * 600)), // 300-900 Hz (mouth opening)
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f2: Math.min(65535, Math.round(800 + centroid * 1800)), // 800-2600 Hz (tongue position)
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f3: Math.min(65535, Math.round(2000 + centroid * 1500)), // 2000-3500 Hz (nasal cavity)
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};
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}
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/**
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* Get codec stats
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*/
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public getStats() {
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return {
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name: 'XCU RESONANCE',
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frameSize: RESONANCE_FRAME_SIZE,
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frameDuration: '20ms',
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bandwidth: '~400 bps',
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compression: '640:10 (64x)',
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method: 'Biomechanical Vocal Tract Synthesis',
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};
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}
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}
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