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Real-TurnTurk: A Multimodal Turkish Corpus for Turn-Taking Prediction — arXiv:2608.22071

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.22071
License (as archived): CC0-1.0
Archived: 2026-10-18T07:42:36.308Z
SHA-256 of the archived text: f6069fe5fab0f660ee9c079e70ca4e38c3aab6e8a6232dd4af872ea878773c89
Stable URL of this page: https://metraipolis.com/documento/dc_a545d652efd7

How to cite

Real-TurnTurk: A Multimodal Turkish Corpus for Turn-Taking Prediction — arXiv:2608.22071 — arXiv (en), https://arxiv.org/abs/2608.22071 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_a545d652efd7 (Metraipolis archive dc_a545d652efd7, sha256 f6069fe5fab0f660ee9c079e70ca4e38c3aab6e8a6232dd4af872ea878773c89)

BibTeX

@misc{dca545d652efd7,
  title = {Real-TurnTurk: A Multimodal Turkish Corpus for Turn-Taking Prediction — arXiv:2608.22071},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.22071},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_a545d652efd7; sha256 f6069fe5fab0f660ee9c079e70ca4e38c3aab6e8a6232dd4af872ea878773c89},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.22071. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

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.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-25 in cs.AI).
Categorie arXiv: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2608.22071 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-18T07:37:52.852Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-25?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).