Card: eot-bench comparison first, charts after the table

README.md

@@ -33,64 +33,7 @@ you want a stricter threshold; otherwise use the tiny model, which we recommend
 
 ## Results
 
-**In a real LiveKit Agents 1.8 pipeline** (Silero VAD → turn detector → endpointing, no STT, 300 recorded
-telephony turns, LiveKit defaults: VAD silence 0.55 s, `min_delay` 0.5 s, `max_delay` 3.0 s):
-
-| turn detector | latency p50 / p90 | turns cut off | finished turns on the fast path | AUC (eot vs hold) |
-|---|---:|---:|---:|---:|
-| VAD only | 0.63 / 0.71 s | 14.3 % | – | – |
-| smart-turn-v3, threshold 0.5 | 0.65 / 3.04 s | 10.0 % | 82 % | 0.74 |
-| tiny variant, threshold 0.5 | 0.64 / 0.74 s | 10.0 % | 95 % | 0.84 |
-| **this model, threshold 0.3** | **0.64 / 0.74 s** | **9.7 %** | **96 %** | **0.88** |
-| this model, threshold 0.5 | 0.65 / 2.93 s | 9.3 % | 90 % | 0.88 |
-
-The int8 export's scores sit a little lower than the tiny model's (recall at 0.5 is 0.87 vs 0.92 at the pause
-start), so **0.3 is this model's equivalent of the tiny model's 0.5**; at 0.5 it is stricter — one more cut-off
-avoided, but 10 % of finished turns wait for `max_delay`. One cut-off turn in 300 separates it from the tiny
-model at matched fast-path share, which is within noise.
-
-**Offline, at fixed cut points relative to the start of each pause** (AUC, same 300 turns, every pause):
-
-| cut relative to pause start | −0.4 s | −0.2 s | 0.0 s | +0.2 s | +0.6 s |
-|---|---:|---:|---:|---:|---:|
-| smart-turn-v3 | 0.60 | 0.62 | 0.63 | 0.65 | 0.69 |
-| tiny variant (int8) | 0.72 | 0.78 | 0.80 | 0.81 | 0.97 |
-| **this model (int8)** | **0.77** | **0.82** | **0.85** | **0.87** | **0.98** |
-
-Score smoothness along a pause matches the tiny model (local std 0.044 over 200 ms, threshold flips 1.7 %
-per 20 ms step; smart-turn-v3 0.124 / 9.8 %).
-
-**Under LiveKit's [eot-bench](https://github.com/livekit/eot-bench) harness** (100 ms causal grid over
-every pause ≥ 0.1 s, `threshold × action_delay × timeout` policy sweep; same adapter for all audio models,
-scored 0.2 s into each pause for the scalar metrics):
-
-| set | model | cutoff @ 300 ms budget | cutoff @ 600 ms | latency @ 5 % cutoff | latency @ 10 % cutoff | AUC |
-|---|---|---:|---:|---:|---:|---:|
-| telephony test, 1 000 turns, English (510 eot / 260 hold spans) | **this model** | **47.3 %** | **25.0 %** | **1 722 ms** | **1 261 ms** | **0.84** |
-| | tiny variant | 50.8 % | 30.0 % | 2 039 ms | 1 529 ms | 0.80 |
-| | smart-turn-v3 | 69.6 % | 35.4 % | 2 269 ms | 1 756 ms | 0.66 |
-| | VAD baseline | 77.3 % | 41.9 % | 2 020 ms | 1 610 ms | – |
-| telephony test, 1 000 turns, Malay (485 / 169) | **this model** | **49.1 %** | **25.4 %** | **1 903 ms** | 1 494 ms | **0.86** |
-| | tiny variant | 55.0 % | 32.5 % | 2 019 ms | **1 423 ms** | 0.81 |
-| | smart-turn-v3 | 78.1 % | 39.1 % | 2 635 ms | 2 116 ms | 0.63 |
-| | VAD baseline | 79.3 % | 46.2 % | 2 540 ms | 2 060 ms | – |
-| telephony, the 300 benchmark turns, English (188 / 105) | **this model** | **45.7 %** | **21.9 %** | **1 530 ms** | **1 151 ms** | **0.83** |
-| | tiny variant | 58.1 % | 27.6 % | 1 636 ms | 1 198 ms | 0.77 |
-| | smart-turn-v3 | 74.3 % | 30.5 % | 1 649 ms | 1 164 ms | 0.64 |
-| | VAD baseline | 77.1 % | 31.4 % | 1 800 ms | 1 510 ms | – |
-| telephony, the 300 benchmark turns, Malay (112 / 35) | **this model** | **48.6 %** | **25.7 %** | **1 761 ms** | **1 238 ms** | **0.85** |
-| | tiny variant | 57.1 % | 31.4 % | 1 843 ms | 1 482 ms | 0.78 |
-| | smart-turn-v3 | 68.6 % | 34.3 % | 2 357 ms | 1 603 ms | 0.63 |
-| | VAD baseline | 80.0 % | 34.3 % | 2 410 ms | 1 830 ms | – |
-
-Where the tiny model only ties the VAD timer on latency at a 5 % cutoff budget, this one is ahead of it on
-every operating point of every subset, and ahead of the tiny model everywhere except latency at 10 % on the
-Malay 1 000-turn set. The harness asks within the first 100–300 ms of every pause, before an audio model has
-silence evidence; the extra encoder capacity buys the most exactly there (AUC 0.85 vs 0.80 at the pause
-start). In the LiveKit pipeline, which asks after the VAD's 0.4–0.55 s of silence, the two are one cut-off
-turn apart.
-
-## Compared with other open detectors (eot-bench, 1 000 telephony turns)
+### Compared with other open detectors (eot-bench, 1 000 telephony turns)
 
 Same harness, same 1 000 random private telephony test turns (both language tags pooled),
 every open audio-native end-of-turn detector we could run
@@ -148,6 +91,65 @@ family, served from a GPU with dynamic batching, and is not public.
 
 ![Operating points across sets and language tags](https://huggingface.co/Scicom-intl/semantic-vad-eot-whisper-base/resolve/main/assets/heatmap.png)
 
+### In the pipeline and at fixed cut points
+
+**In a real LiveKit Agents 1.8 pipeline** (Silero VAD → turn detector → endpointing, no STT, 300 recorded
+telephony turns, LiveKit defaults: VAD silence 0.55 s, `min_delay` 0.5 s, `max_delay` 3.0 s):
+
+| turn detector | latency p50 / p90 | turns cut off | finished turns on the fast path | AUC (eot vs hold) |
+|---|---:|---:|---:|---:|
+| VAD only | 0.63 / 0.71 s | 14.3 % | – | – |
+| smart-turn-v3, threshold 0.5 | 0.65 / 3.04 s | 10.0 % | 82 % | 0.74 |
+| tiny variant, threshold 0.5 | 0.64 / 0.74 s | 10.0 % | 95 % | 0.84 |
+| **this model, threshold 0.3** | **0.64 / 0.74 s** | **9.7 %** | **96 %** | **0.88** |
+| this model, threshold 0.5 | 0.65 / 2.93 s | 9.3 % | 90 % | 0.88 |
+
+The int8 export's scores sit a little lower than the tiny model's (recall at 0.5 is 0.87 vs 0.92 at the pause
+start), so **0.3 is this model's equivalent of the tiny model's 0.5**; at 0.5 it is stricter — one more cut-off
+avoided, but 10 % of finished turns wait for `max_delay`. One cut-off turn in 300 separates it from the tiny
+model at matched fast-path share, which is within noise.
+
+**Offline, at fixed cut points relative to the start of each pause** (AUC, same 300 turns, every pause):
+
+| cut relative to pause start | −0.4 s | −0.2 s | 0.0 s | +0.2 s | +0.6 s |
+|---|---:|---:|---:|---:|---:|
+| smart-turn-v3 | 0.60 | 0.62 | 0.63 | 0.65 | 0.69 |
+| tiny variant (int8) | 0.72 | 0.78 | 0.80 | 0.81 | 0.97 |
+| **this model (int8)** | **0.77** | **0.82** | **0.85** | **0.87** | **0.98** |
+
+Score smoothness along a pause matches the tiny model (local std 0.044 over 200 ms, threshold flips 1.7 %
+per 20 ms step; smart-turn-v3 0.124 / 9.8 %).
+
+**Under LiveKit's [eot-bench](https://github.com/livekit/eot-bench) harness** (100 ms causal grid over
+every pause ≥ 0.1 s, `threshold × action_delay × timeout` policy sweep; same adapter for all audio models,
+scored 0.2 s into each pause for the scalar metrics):
+
+| set | model | cutoff @ 300 ms budget | cutoff @ 600 ms | latency @ 5 % cutoff | latency @ 10 % cutoff | AUC |
+|---|---|---:|---:|---:|---:|---:|
+| telephony test, 1 000 turns, English (510 eot / 260 hold spans) | **this model** | **47.3 %** | **25.0 %** | **1 722 ms** | **1 261 ms** | **0.84** |
+| | tiny variant | 50.8 % | 30.0 % | 2 039 ms | 1 529 ms | 0.80 |
+| | smart-turn-v3 | 69.6 % | 35.4 % | 2 269 ms | 1 756 ms | 0.66 |
+| | VAD baseline | 77.3 % | 41.9 % | 2 020 ms | 1 610 ms | – |
+| telephony test, 1 000 turns, Malay (485 / 169) | **this model** | **49.1 %** | **25.4 %** | **1 903 ms** | 1 494 ms | **0.86** |
+| | tiny variant | 55.0 % | 32.5 % | 2 019 ms | **1 423 ms** | 0.81 |
+| | smart-turn-v3 | 78.1 % | 39.1 % | 2 635 ms | 2 116 ms | 0.63 |
+| | VAD baseline | 79.3 % | 46.2 % | 2 540 ms | 2 060 ms | – |
+| telephony, the 300 benchmark turns, English (188 / 105) | **this model** | **45.7 %** | **21.9 %** | **1 530 ms** | **1 151 ms** | **0.83** |
+| | tiny variant | 58.1 % | 27.6 % | 1 636 ms | 1 198 ms | 0.77 |
+| | smart-turn-v3 | 74.3 % | 30.5 % | 1 649 ms | 1 164 ms | 0.64 |
+| | VAD baseline | 77.1 % | 31.4 % | 1 800 ms | 1 510 ms | – |
+| telephony, the 300 benchmark turns, Malay (112 / 35) | **this model** | **48.6 %** | **25.7 %** | **1 761 ms** | **1 238 ms** | **0.85** |
+| | tiny variant | 57.1 % | 31.4 % | 1 843 ms | 1 482 ms | 0.78 |
+| | smart-turn-v3 | 68.6 % | 34.3 % | 2 357 ms | 1 603 ms | 0.63 |
+| | VAD baseline | 80.0 % | 34.3 % | 2 410 ms | 1 830 ms | – |
+
+Where the tiny model only ties the VAD timer on latency at a 5 % cutoff budget, this one is ahead of it on
+every operating point of every subset, and ahead of the tiny model everywhere except latency at 10 % on the
+Malay 1 000-turn set. The harness asks within the first 100–300 ms of every pause, before an audio model has
+silence evidence; the extra encoder capacity buys the most exactly there (AUC 0.85 vs 0.80 at the pause
+start). In the LiveKit pipeline, which asks after the VAD's 0.4–0.55 s of silence, the two are one cut-off
+turn apart.
+
 ## Files
 
 | file | what |