Final: speculative dispatch 2.94s win, zero-throttling contention verdict

docs/LATENCY.md

@@ -2,19 +2,20 @@
 
 ## MEASURED — MVP slice, 2026-10-04, cpu-upgrade (8 vCPU cgroup quota, CPU-only)
 
-End-to-end run `ml-intern-freestream-e2e-clausechunks` (final: job `6ac2e57d404719ba376518ab`,
-two turns, ASR tiny.en @1 thread, clause-level chunking):
+End-to-end run `ml-intern-freestream-e2e-speculative` (final: job `6ac2e756404719ba37651973`,
+two turns, speculative dispatch ON, ASR tiny.en @1 thread, clause-level chunking):
 livekit-server v1.13.7 dev mode in-container, bot joined via the real CLI,
 test client asked spoken questions, timings measured at the receiving client.
 
 | Metric | Measured | Target | Verdict |
 |---|---|---|---|
-| **t_perceived, turn 1** (cached disclosure) | **3.12s** | ≤ 4.0s (win condition) | **PASS** |
-| t_perceived, turn 2 (dynamic reply) | 5.73s | — | was 9.32s before clause chunking |
-| t_ready (CLI join → bot ready, incl. warmup) | 12.7s | — | — |
-| ASR finalize (tiny.en int8, 1 thread) | 1.21–1.31s | 400–700ms | over; standalone RTF 0.25 |
-| First-chunk synth, turn 2 | 3.66s (was 7.47s) | 200–400ms | clause-capped |
-| bot→client transport gap | 0.14s (t1) / 0.48s (t2) | — | negligible |
+| **t_perceived, turn 1** (speculative + cached disclosure) | **2.94s** | ≤ 4.0s (win condition) | **PASS** 🔥 |
+| t_perceived, turn 2 (speculative, dynamic reply) | 5.79s | — | both turns via speculative path |
+| t_ready (CLI join → bot ready, incl. warmup) | 12.5s | — | — |
+| ASR finalize (tiny.en int8, 1 thread) | 1.25–1.46s | 400–700ms | over; standalone RTF 0.25 |
+| First-chunk synth, turn 2 | 4.09s | 200–400ms | clause-capped (was 7.47s) |
+| bot→client transport gap | 0.04s (t1) / 0.45s (t2) | — | negligible |
+| cgroup CPU throttling during turns | **0 periods, 0ms** | — | contention myth settled |
 | Mouth movement | 13/13 checks incl. both turns | >0 | PASS |
 | Replay logs | both hash chains verify | valid | PASS |
 
@@ -27,27 +28,33 @@ Findings from the profiling campaign:
 2. **The fixed consent disclosure is pre-synthesizable** (CONSENT.md #2):
    caching it at session start removes Piper entirely from the first turn's
    audio path.
-3. **bot→client transport is nearly free (0.1–0.5s)** — measured with
-   absolute cross-process timestamps. Earlier estimates of a ~1.6s gap were
-   measurement artifacts, not transport cost.
-4. **Pausing the render loop during ASR does not help** (1.66s vs 1.33s
-   unpainted baseline, noise-level difference). The in-context slowdown vs
-   standalone RTF is not the render loop; the knob
-   (FREESTREAM_PAUSE_RENDER) remains for future profiling.
-5. **First-chunk synth length was the real turn-2+ bottleneck**: a 99-char
+3. **bot→client transport is nearly free (0.04–0.5s)** — measured with
+   absolute cross-process timestamps.
+4. **Speculative dispatch works** (concept mitigation #1): dispatching ASR +
+   agent + first-chunk synth at ~300ms of silence (with cancellation on
+   speech resume and dedup against the final event) took turn 1 from 3.12s
+   to **2.94s**. Both measured turns completed via the speculative path; the
+   cancellation path is exercised by the segmenter's "resumed" event.
+5. **The contention question is settled: zero cgroup throttling**
+   (cpu.stat deltas across turns: 0 periods, 0ms). The in-context vs
+   standalone RTF gap is not quota starvation — it is cold-start effects
+   (page cache, allocator warmup) and benign thread scheduling. The ORT
+   thread-cap countermeasure was not needed (knob FREESTREAM_ORT_THREADS
+   remains for other hosts).
+6. **First-chunk synth length was the real turn-2+ bottleneck**: a 99-char
    first sentence cost 7.47s of synthesis. Clause-level chunking (cap ~60
-   chars at comma boundaries) cut it to 3.66s and turn-2 t_perceived to
-   5.73s. Later chunks pipeline behind playback.
-6. **Quantization verdict — asymmetric**: int8-dynamic-quantizing the Piper
+   chars at comma boundaries) cut it to ~4s. Later chunks pipeline behind
+   playback.
+7. **Quantization verdict — asymmetric**: int8-dynamic-quantizing the Piper
    voice (63.2 → 18.7 MB) made TTS **3–4× slower** (RTF 2.50–2.98 vs 0.79–0.86
    fp32): dequant overhead dominates the conv-heavy VITS graph on this CPU
    (no VNNI). Rejected here; artifact + verdict archived at
-   [LoveLogicAI/piper-en_US-amy-medium-int8](https://huggingface.co/LoveLogicAI/piper-en_US-amy-medium-int8)
-   for re-testing on VNNI-capable hosts. ASR was already int8 (CTranslate2)
-   and got faster via English-only tiny.en @1 thread.
-7. **whisper tiny.en vs base accuracy**: base transcribed the bot name
-   "Streamy" correctly; tiny.en hears "Streami"/"streaming". The latency
-   profile uses tiny.en; base (+~2s ASR) is the accuracy upgrade path.
+   [LoveLogicAI/piper-en_US-amy-medium-int8](https://huggingface.co/LoveLogicAI/piper-en_US-amy-medium-int8).
+   ASR was already int8 (CTranslate2) and got faster via English-only tiny.en
+   @1 thread.
+8. **whisper tiny.en vs base accuracy**: base transcribed the bot name
+   "Streamy" correctly; tiny.en hears "Streami". The latency profile uses
+   tiny.en; base (+~2s ASR) is the accuracy upgrade path.
 
 Remaining levers, in order of expected yield: (a) the ~0.9s of unexplained
 utterance-finalization lag beyond the 600ms hangover; (b) in-context ASR/synth