feat(calls): integrate verified DTLN and DFN3 ML noise suppression models

- Verified package layouts and integration paths for @workadventure/noise-suppression (v0.0.4) and deepfilternet3-noise-filter (v1.2.1).
- Updated build configuration to correctly copy WASM, TFLite, and ONNX assets.
- Integrated DTLN and DeepFilterNet initialization logic into the audio shim.
- Enabled all four models (RNNoise, Speex, DTLN, DFN3) in Settings UI.

build/lotus-denoise.js

@@ -54,6 +54,14 @@
       script: 'speexWorklet.js',
       wasm: 'speex.wasm',
     },
+    dtln: {
+      name: 'dtln-processor',
+      script: 'dtlnWorklet.js',
+    },
+    deepfilternet: {
+      name: 'deepfilter-audio-processor',
+      script: 'dfn3Worklet.js',
+    },
     gate: {
       name: '@sapphi-red/web-noise-suppressor/noise-gate',
       script: 'noiseGateWorklet.js',
@@ -148,14 +156,31 @@
         }
 
         // 2. ML Processor
-        var mlNode = new AudioWorkletNode(ctx, PROCESSORS[MODEL].name, {
+        var mlOptions = {
           channelCount: 1,
-          channelCountMode: 'explicit',
           numberOfInputs: 1,
           numberOfOutputs: 1,
-          outputChannelCount: [1],
-          processorOptions: { maxChannels: 1, wasmBinary: wasmBinary },
-        });
+          processorOptions: { maxChannels: 1 }
+        };
+
+        if (MODEL === 'rnnoise' || MODEL === 'speex') {
+          mlOptions.processorOptions.wasmBinary = wasmBinary;
+        } else if (MODEL === 'dtln') {
+          mlOptions.processorOptions = {
+            wasmUrl: ASSET_BASE + 'litert_wasm_internal.wasm',
+            model1Url: ASSET_BASE + 'model_1.tflite',
+            model2Url: ASSET_BASE + 'model_2.tflite',
+            processorUrl: ASSET_BASE + 'dtlnProcessor.js'
+          };
+        } else if (MODEL === 'deepfilternet') {
+          mlOptions.processorOptions = {
+            wasmModule: wasmBinary,
+            modelBytes: new Uint8Array(wasmBinary),
+            suppressionLevel: 50
+          };
+        }
+
+        var mlNode = new AudioWorkletNode(ctx, PROCESSORS[MODEL].name, mlOptions);
         head.connect(mlNode);
         mlNode.connect(dest);