fix(calls): finalize DTLN integration, stabilize build, and fix formatting

build/lotus-denoise.js

@@ -54,6 +54,10 @@
       script: 'speexWorklet.js',
       wasm: 'speex.wasm',
     },
+    dtln: {
+      name: 'noise-suppression-audio-worklet',
+      script: 'dtlnWorklet.js',
+    },
     gate: {
       name: '@sapphi-red/web-noise-suppressor/noise-gate',
       script: 'noiseGateWorklet.js',
@@ -115,6 +119,7 @@
         }
         // Load required modules
         var scripts = [PROCESSORS[MODEL].script];
+        if (MODEL === 'dtln') scripts.push('dtlnProcessor.js');
         if (USE_GATE) scripts.push(PROCESSORS.gate.script);
 
         return Promise.all(
@@ -166,14 +171,24 @@
         }
 
         // 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 = {
+            wasmBinary: wasmBinary,
+            model1: ASSET_BASE + 'model_1.tflite',
+            model2: ASSET_BASE + 'model_2.tflite',
+          };
+        }
+
+        var mlNode = new AudioWorkletNode(ctx, PROCESSORS[MODEL].name, mlOptions);
         head.connect(mlNode);
         mlNode.connect(dest);