fix: ground threshold tuning in ambient evidence

docs/CLI.md

@@ -13,7 +13,9 @@ bargekit fixtures --json
 
 ## `bargekit tune`
 
-Analyze a fixture and print threshold guidance.
+Analyze a fixture and print threshold guidance. The report separates the highest
+ambient level below the configured speech threshold (`peakNoiseLevel`) from the
+average level of frames classified as speech (`averageSpeechLevel`).
 
 ```sh
 bargekit tune --fixture tests/fixtures/long_utterance.json

src/fixtures.js

@@ -117,6 +117,7 @@ export function analyzeFixtureForThresholds(fixture, overrides = {}) {
   let noiseFrames = 0;
   let quietFrames = 0;
   let peakLevel = 0;
+  let peakNoiseLevel = 0;
 
   for (const sample of fixture.samples) {
     peakLevel = Math.max(peakLevel, sample.level);
@@ -125,6 +126,7 @@ export function analyzeFixtureForThresholds(fixture, overrides = {}) {
       continue;
     }
 
+    peakNoiseLevel = Math.max(peakNoiseLevel, sample.level);
     if (sample.level >= config.noiseFloorThreshold) {
       noiseFrames += 1;
       continue;
@@ -139,7 +141,8 @@ export function analyzeFixtureForThresholds(fixture, overrides = {}) {
       .reduce((sum, sample) => sum + sample.level, 0) / speechFrames;
 
   const suggestedProfile = Object.entries(PRESET_PROFILES).reduce((best, [name, profile]) => {
-    const distance = Math.abs(profile.speechThreshold - averageSpeechLevel || config.speechThreshold);
+    const comparisonLevel = averageSpeechLevel || config.speechThreshold;
+    const distance = Math.abs(profile.speechThreshold - comparisonLevel);
     if (!best || distance < best.distance) {
       return { name, distance };
     }
@@ -152,6 +155,7 @@ export function analyzeFixtureForThresholds(fixture, overrides = {}) {
     noiseFrames,
     quietFrames,
     peakLevel,
+    peakNoiseLevel,
     averageSpeechLevel,
     suggestedProfile,
     explanation: speechFrames === 0

src/tuning.js

@@ -3,13 +3,16 @@ import { analyzeFixtureForThresholds } from './fixtures.js';
 
 export function recommendThresholds(fixtures, options = {}) {
   const analyses = fixtures.map((fixture) => analyzeFixtureForThresholds(fixture, options));
-  const peaks = analyses.map((analysis) => analysis.peakLevel).filter((level) => level > 0).sort((a, b) => a - b);
+  const noisePeaks = analyses
+    .map((analysis) => analysis.peakNoiseLevel)
+    .filter((level) => level > 0)
+    .sort((a, b) => a - b);
   const speechAverages = analyses
     .map((analysis) => analysis.averageSpeechLevel)
     .filter((level) => level > 0)
     .sort((a, b) => a - b);
 
-  const noiseCeiling = percentile(peaks, 0.5) || DEFAULT_CONFIG.noiseFloorThreshold;
+  const noiseCeiling = percentile(noisePeaks, 0.5) || DEFAULT_CONFIG.noiseFloorThreshold;
   const speechFloor = percentile(speechAverages, 0.25) || DEFAULT_CONFIG.speechThreshold;
   const speechThreshold = clamp(round(Math.max(speechFloor * 0.82, noiseCeiling + 0.18)), 0.2, 0.9);
   const noiseFloorThreshold = clamp(round(Math.min(noiseCeiling + 0.04, speechThreshold - 0.1)), 0.04, 0.5);

test/fixtures.test.js

@@ -28,6 +28,7 @@ test('tuning analysis explains threshold decisions and suggests a profile', () =
   });
 
   assert.equal(analysis.speechFrames, 0);
+  assert.equal(analysis.peakNoiseLevel, 0.23);
   assert.match(analysis.explanation, /No speech crossed/);
   assert.ok(analysis.suggestedProfile);
 });

test/tuning.test.js

@@ -1,10 +1,30 @@
 import assert from 'node:assert/strict';
 import { test } from 'node:test';
-import { SYNTHETIC_FIXTURES, recommendThresholds } from '../src/index.js';
+import {
+  SYNTHETIC_FIXTURES,
+  analyzeFixtureForThresholds,
+  createSyntheticFixture,
+  recommendThresholds
+} from '../src/index.js';
 
-test('threshold recommendation returns safe ordered thresholds and rationale', () => {
+test('threshold recommendation separates ambient peaks from speech evidence', () => {
   const result = recommendThresholds([SYNTHETIC_FIXTURES.keyboard_noise, SYNTHETIC_FIXTURES.long_utterance]);
-  assert.ok(result.config.speechThreshold > result.config.noiseFloorThreshold);
-  assert.ok(result.closestProfile);
+  assert.equal(result.config.speechThreshold, 0.59);
+  assert.equal(result.config.noiseFloorThreshold, 0.27);
+  assert.equal(result.analyses[0].peakNoiseLevel, 0.23);
+  assert.ok(Math.abs(result.analyses[1].averageSpeechLevel - 0.72) < Number.EPSILON * 4);
+  assert.equal(result.closestProfile, 'laptop_speakers');
   assert.match(result.rationale, /speechThreshold/);
 });
+
+test('profile selection preserves zero distance for an exact speech threshold match', () => {
+  const fixture = createSyntheticFixture('exact-wired-headset', {
+    baseline: 0.04,
+    segments: [{ startMs: 100, endMs: 300, level: 0.5 }]
+  });
+
+  const analysis = analyzeFixtureForThresholds(fixture, { speechThreshold: 0.5 });
+
+  assert.equal(analysis.averageSpeechLevel, 0.5);
+  assert.equal(analysis.suggestedProfile, 'wired_headset');
+});