docs/LATENCY.md

LATENCY — benchmarking methods & budget tables

MEASURED — MVP slice, 2026-10-04, cpu-upgrade (8 vCPU cgroup quota, CPU-only)

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 (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_perceived, roleplay mode (LLM agent in the loop)	7.1–7.4s	relaxed (12s)	HF router generation dominates
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

Findings from the profiling campaign:

1. cgroup oversubscription is the #1 CPU pitfall: the container reports os.cpu_count()=64 under an 8-core quota. Whisper tiny at 8 threads measured 39.5s vs 1.16s at 1 thread (same transcript). Thread counts are pinned low (FREESTREAM_WHISPER_THREADS).
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 (0.04–0.5s) — 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 ~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. 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 contention (standalone RTF 0.25/0.79 vs in-context ~0.5/1.2) — the render loop is exonerated, so the suspect is WebRTC encode + thread interference; (c) the concept's speculative dispatch at ~600ms silence (overlaps agent response with utterance tail) — the largest structural win for turn-2+, but a bigger build.

The tables below are the original design targets, kept for reference.

Budget (from the concept package; measured results above)

These are the targets the MVP slice was designed against; the MEASURED section above is the current scorecard against them.

Stage	Local CPU-only	Local + GPU/ANE	Pika (published)
ASR finalize	400–700ms	150–250ms	—
Agent first token	300–900ms	150–400ms	—
TTS first chunk	200–400ms	80–150ms	—
Avatar render	500–900ms	200–350ms	—
Perceived turn	~2.5–4.5s	~1.2–2.0s	~1.5s

The mitigations that make 2.5s feel like 1.5s

1. Speculative dispatch at ~600ms of silence — partial ASR transcripts go to the agent before the utterance finalizes; resumed speech cancels the generation. Saves 200–600ms.
2. Sentence-level pre-roll — the agent's first sentence starts TTS while later sentences are still generating. Saves one TTS round-trip.
3. Lead-out motion — avatar mouth motion starts ~150ms before audio playout, perceptually erasing the render handshake.
4. Cached identity — avatar/voice assets are loaded and warmed at session start, never per turn.

Fidelity ladder rungs & FPS targets

Rung	Name	Target FPS	Host
4	FULL_PORTRAIT	20–24	GPU / Apple ANE
3	VISEME_STILL	≥15 (MVP)	CPU
2	AUDIO_REACTIVE_WAVE	≥10	CPU (weak)
1	STATIC_CARD	n/a	anything

Rung selection is select_rung() at join time; runtime degradation triggers when measured FPS < target for 5 consecutive seconds (event: persona.rung_change).

Benchmark harness (MVP acceptance)

python benchmarks/turn_latency.py (lands with the MVP slice) measures, per turn over ≥50 synthetic Q&A turns:

• t_asr_final: speech-end → final transcript
• t_first_token: transcript → agent first sentence
• t_tts_chunk: sentence → first audio chunk
• t_avatar_frame: audio chunk → first frame on the virtual camera
• t_perceived: speech-end → first audible+visible output

Win condition from the concept: agent joins, answers within 4s with a moving mouth, leaves, and produces a valid replay log — i.e. t_perceived p50 < 4.0s on CPU at rung 3, and EventLog(...).verify() == (True, None).

Reporting rules

• Report p50/p95, machine, and library versions with every number.
• Faster-whisper int8, Piper medium voices; note thread counts.
• If FULL_PORTRAIT can't hold 20 FPS on Apple Silicon, video becomes a cloud-burst feature and rung 3 becomes the local ceiling — that is a finding to report, not a failure to hide.