Add transcription settings management and UI controls

components/SettingsMenu.tsx

@@ -28,6 +28,33 @@ const MENU_LINKS = [
   { label: "Follow on X", href: X_PROFILE_URL, Icon: XIcon },
 ] as const;
 
+const TRANSCRIPTION_SETTINGS_STORAGE_KEY = "rescript.transcription.settings";
+const DEFAULT_TRANSCRIPTION_SETTINGS = {
+  maxSpeakers: 2,
+  onsetThreshold: 0.7,
+};
+
+function readTranscriptionSettings() {
+  if (typeof window === "undefined" || !window.localStorage) {
+   return DEFAULT_TRANSCRIPTION_SETTINGS;
+  }
+  try {
+   const raw = window.localStorage.getItem(TRANSCRIPTION_SETTINGS_STORAGE_KEY);
+   if (!raw) return DEFAULT_TRANSCRIPTION_SETTINGS;
+   const parsed = JSON.parse(raw) as Partial<typeof DEFAULT_TRANSCRIPTION_SETTINGS>;
+   return {
+     maxSpeakers: Number.isFinite(parsed.maxSpeakers)
+       ? Math.max(1, Math.round(Number(parsed.maxSpeakers)))
+       : DEFAULT_TRANSCRIPTION_SETTINGS.maxSpeakers,
+     onsetThreshold: Number.isFinite(parsed.onsetThreshold)
+       ? Math.max(0, Math.min(1, Number(parsed.onsetThreshold)))
+       : DEFAULT_TRANSCRIPTION_SETTINGS.onsetThreshold,
+   };
+  } catch {
+   return DEFAULT_TRANSCRIPTION_SETTINGS;
+  }
+}
+
 /**
  * Top-bar settings popover. Houses appearance, transcript source, and social
  * links for now — structure is section-based so more prefs can land here later.
@@ -37,6 +64,30 @@ export default function SettingsMenu() {
   const panelId = useId();
   const { appearance, setAppearance } = useAppearance();
   const { enabled: telemetry, setEnabled: setTelemetry } = useTelemetryPref();
+  const [transcriptionSettings, setTranscriptionSettings] = useState(() =>
+    readTranscriptionSettings()
+  );
+
+  const commitTranscriptionSettings = (
+    patch: Partial<typeof DEFAULT_TRANSCRIPTION_SETTINGS>
+  ) => {
+    const next = { ...transcriptionSettings, ...patch };
+    const normalized = {
+      maxSpeakers: Math.max(1, Math.round(Number(next.maxSpeakers))),
+      onsetThreshold: Math.max(0, Math.min(1, Number(next.onsetThreshold))),
+    };
+    setTranscriptionSettings(normalized);
+    try {
+      if (typeof window !== "undefined") {
+        window.localStorage.setItem(
+          TRANSCRIPTION_SETTINGS_STORAGE_KEY,
+          JSON.stringify(normalized)
+        );
+      }
+    } catch {
+      // localStorage may be unavailable in private browsing or storage-full modes.
+    }
+  };
 
   return (
     <Popover
@@ -93,6 +144,49 @@ export default function SettingsMenu() {
             </div>
           </section>
 
+          <section className="border-b border-zinc-100 px-3 py-2.5 dark:border-zinc-800">
+            <p className="mb-2 text-[11px] font-medium tracking-wide text-zinc-400 dark:text-zinc-500">
+              Transcription
+            </p>
+            <div className="space-y-2">
+              <label className="block">
+                <span className="mb-1 block text-[11px] font-medium text-zinc-500 dark:text-zinc-400">
+                  Max speakers
+                </span>
+                <input
+                  type="number"
+                  min={1}
+                  max={8}
+                  value={transcriptionSettings.maxSpeakers}
+                  onChange={(e) =>
+                    commitTranscriptionSettings({
+                      maxSpeakers: Number(e.target.value || 1),
+                    })
+                  }
+                  className="w-full rounded-md border border-zinc-200 bg-white px-2 py-1 text-[12px] outline-none focus:border-zinc-500 dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100"
+                />
+              </label>
+              <label className="block">
+                <span className="mb-1 block text-[11px] font-medium text-zinc-500 dark:text-zinc-400">
+                  Onset threshold
+                </span>
+                <input
+                  type="number"
+                  min={0}
+                  max={1}
+                  step={0.05}
+                  value={transcriptionSettings.onsetThreshold}
+                  onChange={(e) =>
+                    commitTranscriptionSettings({
+                      onsetThreshold: Number(e.target.value || 0),
+                    })
+                  }
+                  className="w-full rounded-md border border-zinc-200 bg-white px-2 py-1 text-[12px] outline-none focus:border-zinc-500 dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100"
+                />
+              </label>
+            </div>
+          </section>
+
           <section className="border-b border-zinc-100 px-1.5 py-1.5 dark:border-zinc-800">
             {MENU_LINKS.map(({ label, href, Icon }) => (
               <a

hooks/useTranscriber.ts

@@ -9,6 +9,33 @@ import type { WorkerResponse } from "@/lib/types";
 
 let activeWorker: Worker | null = null;
 
+const TRANSCRIPTION_SETTINGS_KEY = "rescript.transcription.settings";
+const DEFAULT_TRANSCRIPTION_SETTINGS = {
+  maxSpeakers: 2,
+  onsetThreshold: 0.7,
+};
+
+function readTranscriptionSettings() {
+  if (typeof window === "undefined" || !window.localStorage) {
+    return DEFAULT_TRANSCRIPTION_SETTINGS;
+  }
+  try {
+    const raw = window.localStorage.getItem(TRANSCRIPTION_SETTINGS_KEY);
+    if (!raw) return DEFAULT_TRANSCRIPTION_SETTINGS;
+    const parsed = JSON.parse(raw) as Partial<typeof DEFAULT_TRANSCRIPTION_SETTINGS>;
+    return {
+      maxSpeakers: Number.isFinite(parsed.maxSpeakers)
+        ? Math.max(1, Math.round(Number(parsed.maxSpeakers)))
+        : DEFAULT_TRANSCRIPTION_SETTINGS.maxSpeakers,
+      onsetThreshold: Number.isFinite(parsed.onsetThreshold)
+        ? Math.max(0, Math.min(1, Number(parsed.onsetThreshold)))
+        : DEFAULT_TRANSCRIPTION_SETTINGS.onsetThreshold,
+    };
+  } catch {
+    return DEFAULT_TRANSCRIPTION_SETTINGS;
+  }
+}
+
 /** Stop an in-flight ASR job (e.g. after importing a transcript). */
 export function cancelTranscription() {
   activeWorker?.terminate();
@@ -90,13 +117,22 @@ export function useTranscriber() {
       );
     };
 
+    const settings = readTranscriptionSettings();
+
     // Transfer, not copy: the worker takes ownership of the PCM and `audio` is
     // detached here. Nothing on the main thread reads it afterwards — the
     // waveform draws from the envelope the store built in setAudio — and on a
     // long recording the copy this replaces was hundreds of megabytes held for
     // the length of the run.
     workerRef.current.postMessage(
-      { audio, duration, model, language: transcriptLanguage },
+      {
+        audio,
+        duration,
+        model,
+        language: transcriptLanguage,
+        maxSpeakers: settings.maxSpeakers,
+        onsetThreshold: settings.onsetThreshold,
+      },
       [audio.buffer]
     );
   }, []);

lib/types.ts

@@ -104,4 +104,8 @@ export interface WorkerRequest {
    * and is passed through for Parakeet alignment (Parakeet ASR still auto-detects).
    */
   language: import("./languages").TranscriptLanguage;
+  /** Optional speaker-cap setting for diarization post-processing. */
+  maxSpeakers?: number;
+  /** Optional diarization onset confidence threshold. */
+  onsetThreshold?: number;
 }

workers/transcription.worker.ts

@@ -132,6 +132,10 @@ if (/apple/i.test(navigator.vendor)) {
 
 const DIARIZATION_MODEL = "onnx-community/pyannote-segmentation-3.0";
 const VAD_MODEL = "onnx-community/silero-vad";
+/** Limit diarized speaker IDs to the requested UI-friendly headroom. */
+const MAX_ALLOWED_SPEAKERS = 2;
+/** Raise the diarization onset confidence bar above the default soft-slice margin. */
+const ONSET_THRESHOLD = 0.7;
 /** Viterbi needs a frames x tokens lattice, so alignment runs in bounded batches. */
 const ALIGN_BATCH_MAX_S = 20;
 /** Context either side of a batch, so edge words are not clipped. */
@@ -984,14 +988,18 @@ async function refineWordTimestamps(
  * class indices are only meaningful within a pass, which is what the overlap and
  * `stitchDiarizationWindows` are for.
  */
-async function diarize(audio: Float32Array): Promise<DiarizationSegment[]> {
+async function diarize(
+  audio: Float32Array,
+  onsetThreshold = ONSET_THRESHOLD
+): Promise<DiarizationSegment[]> {
   const { processor, model } = await getDiarizer();
   // post_process_speaker_diarization is specific to the PyAnnote processor
   // and is not part of the generic Processor typings.
   const pyannote = processor as unknown as {
     post_process_speaker_diarization: (
       logits: unknown,
-      numSamples: number
+      numSamples: number,
+      opts?: { onsetThreshold?: number; onset_threshold?: number }
     ) => DiarizationSegment[][];
   };
 
@@ -1007,7 +1015,11 @@ async function diarize(audio: Float32Array): Promise<DiarizationSegment[]> {
     windows.push({
       offsetS: startSample / VAD_SAMPLE_RATE,
       durationS: slice.length / VAD_SAMPLE_RATE,
-      segments: pyannote.post_process_speaker_diarization(logits, slice.length)[0] ?? [],
+      segments:
+        pyannote.post_process_speaker_diarization(logits, slice.length, {
+          onsetThreshold,
+          onset_threshold: onsetThreshold,
+        })[0] ?? [],
     });
     postLive({
       type: "progress",
@@ -1019,7 +1031,11 @@ async function diarize(audio: Float32Array): Promise<DiarizationSegment[]> {
 }
 
 /** Assign a speaker to each word from the diarization segments. */
-function assignSpeakers(words: Word[], segments: DiarizationSegment[]) {
+function assignSpeakers(
+  words: Word[],
+  segments: DiarizationSegment[],
+  maxSpeakers = MAX_ALLOWED_SPEAKERS
+) {
   // Segment id 0 is "no speaker" (silence/noise); ignore it.
   const speech = segments.filter((s) => s.id !== 0);
   if (speech.length === 0) {
@@ -1033,6 +1049,7 @@ function assignSpeakers(words: Word[], segments: DiarizationSegment[]) {
   const byStart = [...speech].sort((a, b) => a.start - b.start);
   let cursor = 0;
 
+  const normalizedMax = Math.max(1, Math.round(maxSpeakers));
   const idMap = new Map<number, number>(); // pyannote id -> sequential index
   for (const w of words) {
     const mid = (w.start + w.end) / 2;
@@ -1057,7 +1074,10 @@ function assignSpeakers(words: Word[], segments: DiarizationSegment[]) {
       }
     }
     const raw = seg ? seg.id : -1;
-    if (raw >= 0 && !idMap.has(raw)) idMap.set(raw, idMap.size);
+    if (raw >= 0 && !idMap.has(raw)) {
+      const speakerId = (parseInt(String(raw), 10) % normalizedMax) + 1;
+      idMap.set(raw, speakerId);
+    }
     w.speaker = raw >= 0 ? (idMap.get(raw) as number) : 0;
   }
 }
@@ -1107,12 +1127,14 @@ function wordsFromParakeet(
 
 async function finishWithDiarization(
   words: Word[],
-  audio: Float32Array
+  audio: Float32Array,
+  onsetThreshold = ONSET_THRESHOLD,
+  maxSpeakers = MAX_ALLOWED_SPEAKERS
 ): Promise<Word[]> {
   try {
     post({ type: "progress", message: "Identifying speakers…", value: 0 });
-    const segments = await diarize(audio);
-    assignSpeakers(words, segments);
+    const segments = await diarize(audio, onsetThreshold);
+    assignSpeakers(words, segments, maxSpeakers);
   } catch (err) {
     console.warn("Speaker diarization failed; using a single speaker.", err);
   }
@@ -1122,7 +1144,9 @@ async function finishWithDiarization(
 async function runParakeet(
   audio: Float32Array,
   duration: number,
-  transcriptLanguage: TranscriptLanguage
+  transcriptLanguage: TranscriptLanguage,
+  maxSpeakers = MAX_ALLOWED_SPEAKERS,
+  onsetThreshold = ONSET_THRESHOLD
 ): Promise<Word[]> {
   // Overlap diarizer (+ language-matched aligner) with Parakeet load.
   getDiarizer().catch(() => {});
@@ -1201,14 +1225,16 @@ async function runParakeet(
     duration,
     transcriptLanguage
   );
-  return finishWithDiarization(words, audio);
+  return finishWithDiarization(words, audio, onsetThreshold, maxSpeakers);
 }
 
 async function runWhisper(
   audio: Float32Array,
   duration: number,
   choice: WhisperModel,
-  transcriptLanguage: TranscriptLanguage
+  transcriptLanguage: TranscriptLanguage,
+  maxSpeakers = MAX_ALLOWED_SPEAKERS,
+  onsetThreshold = ONSET_THRESHOLD
 ): Promise<Word[]> {
   // Overlap Whisper + Silero downloads; diarizer and language-matched aligner
   // warm in the background so both are cached by the time the transcript lands.
@@ -1402,20 +1428,39 @@ async function runWhisper(
     transcriptLanguage
   );
 
-  return finishWithDiarization(words, audio);
+  return finishWithDiarization(words, audio, onsetThreshold, maxSpeakers);
 }
 
 self.onmessage = async (event: MessageEvent<WorkerRequest>) => {
-  const { audio, duration, model, language } = event.data;
+  const { audio, duration, model, language, maxSpeakers, onsetThreshold } = event.data;
   try {
     const choice: ModelId = model ?? "base";
     const transcriptLanguage: TranscriptLanguage = language ?? "en";
+    const normalizedMaxSpeakers = Number.isFinite(maxSpeakers)
+      ? Math.max(1, Math.round(Number(maxSpeakers)))
+      : MAX_ALLOWED_SPEAKERS;
+    const normalizedThreshold = Number.isFinite(onsetThreshold)
+      ? Math.max(0, Math.min(1, Number(onsetThreshold)))
+      : ONSET_THRESHOLD;
 
     let words: Word[];
     if (isParakeetModel(choice)) {
-      words = await runParakeet(audio, duration, transcriptLanguage);
+      words = await runParakeet(
+        audio,
+        duration,
+        transcriptLanguage,
+        normalizedMaxSpeakers,
+        normalizedThreshold
+      );
     } else if (isWhisperModel(choice)) {
-      words = await runWhisper(audio, duration, choice, transcriptLanguage);
+      words = await runWhisper(
+        audio,
+        duration,
+        choice,
+        transcriptLanguage,
+        normalizedMaxSpeakers,
+        normalizedThreshold
+      );
     } else {
       throw new Error(`Unknown speech model: ${String(choice)}`);
     }