Publish voice duplex architecture latency training and evaluation research

model.test.mjs

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+import test from "node:test";
+import assert from "node:assert/strict";
+import { queueSteps, benchmarks } from "./model.js";
+
+test("faster processing leaves no waiting queue", () => {
+  const steps = queueSteps(160, 80);
+  assert.equal(steps[0].arrival, 160);
+  assert.equal(steps[0].end, 240);
+  assert.ok(steps.every((step) => step.wait === 0));
+});
+test("equal processing and media intervals leave zero ideal headroom", () => {
+  assert.ok(queueSteps(160, 160).every((step) => step.wait === 0));
+});
+test("overload adds sixty milliseconds per subsequent input block", () => {
+  const steps = queueSteps(160, 220);
+  assert.equal(steps[0].wait, 0);
+  assert.equal(steps[7].wait, 420);
+  assert.equal(steps[7].end, 1920);
+});
+test("invalid media times fail explicitly", () => {
+  assert.throws(() => queueSteps(0, 80), RangeError);
+  assert.throws(() => queueSteps(160, Number.NaN), RangeError);
+});
+test("benchmark ordering and source values are preserved", () => {
+  assert.deepEqual(
+    benchmarks.map((model) => model.answer),
+    [10.12, 8.4, 6.89, 4.25],
+  );
+  assert.ok(benchmarks.every((model) => model.first <= model.answer));
+});