card: overlap measured at segment vs VAD level, related-links wording

README.md

@@ -144,8 +144,9 @@ no speaker-error rate to propagate.
 ### Boundaries and cutting
 
 Turn boundaries come from Silero VAD run per leg, not from transcript
-timestamps: the shipped segments are padded and sum to ~107% of call
-wall-clock, so their edges are not turn boundaries. Transcripts are used only
+timestamps: the shipped segments are padded — cross-channel overlap reads 28.1%
+of speech at segment level against 9.4% measured from VAD spans on the same
+audio — so their edges are not turn boundaries. Transcripts are used only
 at build time — filtering crosstalk bleed, counting words for the backchannel
 gate, and separating mid-segment boundaries — and are never part of a clip.
 
@@ -240,5 +241,5 @@ above reproduces from a clone with no audio and no GPU.
 |---|---|
 | [`santhosh-005/tamil-turns`](https://huggingface.co/datasets/santhosh-005/tamil-turns) | the same calls as whole turns with silence structure — **for turn-taking, pauses, overlap and timing** |
 | [`santhosh-005/smart-turn-tamil`](https://huggingface.co/santhosh-005/smart-turn-tamil) | the end-of-turn model trained on this dataset |
-| [`smart-turn-livekit`](https://pypi.org/project/smart-turn-livekit/) | that model as a LiveKit Agents plugin |
-| [github.com/santhosh-005/tamil-eot](https://github.com/santhosh-005/tamil-eot) | how all of it was built, including the experiments that failed |
+| [`smart-turn-livekit`](https://pypi.org/project/smart-turn-livekit) | LiveKit Agents plugin for Smart Turn architecture models |
+| [`github.com/santhosh-005/tamil-eot`](https://github.com/santhosh-005/tamil-eot) | how all of it was built, including the experiments that failed |