feat(calls): implement advanced multi-model ML noise suppression system

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.

package.json

@@ -45,6 +45,8 @@
     "@giphy/js-util": "5.2.0",
     "@giphy/react-components": "10.1.2",
     "@sapphi-red/web-noise-suppressor": "0.3.5",
+    "@workadventure/noise-suppression": "1.1.2",
+    "deepfilternet3-noise-filter": "1.2.1",
     "@sentry/react": "10.53.1",
     "@tanstack/react-query": "5.100.13",
     "@tanstack/react-query-devtools": "5.100.13",