Paper Detail
Ahmet Tuğrul Bayrak, Fatma Nur Korkmaz, Bekir Berker Türker, Mustafa Sertaç Türkel, Alper Kaplan
Turn-taking is a basic organizational feature of human conversation and remains difficult to model in natural, synchronous dialog systems. While existing research has explored multimodal approaches and large language models for turn-ending prediction, there is a lack of naturalistic conversational corpora specifically addressing turn-taking dynamics in Turkish. This study introduces a multimodal Turkish conversational dataset of unscripted dyadic interactions, comprising synchronized front-facing video, per-speaker audio channels that allow overlapping speech to be attributed to individual speakers, and time-aligned transcriptions. Turn-taking prediction is formulated as a binary classification problem, and a Genetic Algorithm (GA) is employed to optimize interpretable decision rules derived from visual, acoustic, and linguistic features. A hybrid AND-OR rule representation is adopted in the proposed framework to represent the alternative cue combinations that precede a turn transition.
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@misc{bayrak2026real,
title = {Real-TurnTurk: A Multimodal Turkish Corpus for Turn-Taking Prediction},
author = {Ahmet Tuğrul Bayrak and Fatma Nur Korkmaz and Bekir Berker Türker and Mustafa Sertaç Türkel and Alper Kaplan},
year = {2026},
abstract = {Turn-taking is a basic organizational feature of human conversation and remains difficult to model in natural, synchronous dialog systems. While existing research has explored multimodal approaches and large language models for turn-ending prediction, there is a lack of naturalistic conversational corpora specifically addressing turn-taking dynamics in Turkish. This study introduces a multimodal Turkish conversational dataset of unscripted dyadic interactions, comprising synchronized front-facin},
url = {https://huggingface.co/papers/2608.22071},
keywords = {turn-taking prediction, multimodal dataset, Genetic Algorithm, AND-OR rule representation, visual features, acoustic features, linguistic features, Turkish conversational corpus, huggingface daily},
eprint = {2608.22071},
archiveprefix = {arXiv},
}
{}