jared
5d5f5f4516
Implement a flexible, multi-model noise suppression pipeline for Element Call/LiveKit integration: - ML Engines: Added support for RNNoise, Speex, DTLN, and DeepFilterNet 3 models. - Pipeline Architecture: Implemented modular audio processing in lotus-denoise.js, supporting 'Series Suppression' (running browser-native NSNet2 before ML) and a hardware-style Noise Gate. - UI & UX Enhancements: - Settings UI: Added model comparison chart with CPU/Quality metadata. - Tuning: Added Live Microphone Meter for calibrating Noise Gate thresholds. - Reporting: Added LotusToast system to alert users when ML suppression fails or falls back to raw input. - Robustness & Quality: - Capture Fidelity: Removed forced 48kHz capture constraints to allow native-rate capture (solving static issues with high-end audio interfaces). - Performance: Added WASM SIMD detection with transparent fallback. - Capability Detection: Added browser feature detection to disable unsupported ML modes. - Build Integration: Updated Vite config to self-host all model WASM/tflite assets in /denoise/ directory.
69 lines
1.9 KiB
TypeScript
69 lines
1.9 KiB
TypeScript
/**
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* Detection utilities for Lotus ML noise suppression (RNNoise).
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*/
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export type DenoiseModel = {
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id: string;
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name: string;
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description: string;
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cpuUsage: string;
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binarySize: string;
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transients: 'Poor' | 'Good' | 'Excellent';
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voiceQuality: 'Moderate' | 'High' | 'Very High';
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};
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export const DENOISE_MODELS: DenoiseModel[] = [
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{
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id: 'rnnoise',
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name: 'RNNoise (Mozilla)',
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description: 'Lightweight hybrid model. Best for consistent noise like fans.',
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cpuUsage: '< 5%',
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binarySize: '< 1 MB',
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transients: 'Poor',
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voiceQuality: 'Moderate',
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},
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{
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id: 'dtln',
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name: 'DTLN (Balanced)',
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description: 'Deep learning model with a good balance of quality and CPU.',
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cpuUsage: '10-20%',
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binarySize: '3-4 MB',
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transients: 'Good',
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voiceQuality: 'High',
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},
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{
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id: 'deepfilternet',
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name: 'DeepFilterNet 3 (Pro)',
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description: 'State-of-the-art studio quality. Removes all background noise.',
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cpuUsage: '25-50%+',
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binarySize: '15-20 MB',
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transients: 'Excellent',
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voiceQuality: 'Very High',
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},
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];
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export const isMLDenoiseSupported = (): boolean => {
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if (typeof window === 'undefined') return false;
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// Requirements:
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// 1. AudioContext/webkitAudioContext (Web Audio API)
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// 2. AudioWorklet (Real-time processing in a background thread)
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// 3. getUserMedia (Microphone access)
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const hasAudioContext = !!(window.AudioContext || (window as any).webkitAudioContext);
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const hasAudioWorklet = hasAudioContext && !!AudioWorkletNode;
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const hasGetUserMedia = !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia);
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return hasAudioWorklet && hasGetUserMedia;
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};
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/**
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* EXACT requirements for ML Denoise (for UI display).
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*/
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export const ML_DENOISE_REQUIREMENTS = [
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'Modern browser with Web Audio API support',
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'AudioWorklet support (Chrome 66+, Firefox 76+, Safari 14.1+)',
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'Microphone access',
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'48kHz AudioContext capability',
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];
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