Modeling Turn-Taking Speed and Speaker Characteristics (2025)

Abstract: Modeling turn-taking speed while considering speaker characteristics and the relationships between speakers is essential for realizing dialogue systems capable of natural interactions. In this study, we focused on dialogue participants’ roles, relationships, and personality, analyzing and modeling turn-taking speeds observed in real conversations. The analysis confirmed that the expression of these attributes—role, relationship, and personality—is closely associated with turn-taking speed. Based on these findings, we constructed a model that predicts the distribution of turn-taking speeds according to each attribute using a gamma distribution. Evaluation results demonstrated that appropriate parameter fitting to the three-parameter gamma distribution enables effective modeling of turn-taking speeds based on participants’ roles, relationships, and characteristics.

## introduction in conversation, turn-taking refers to the process encompassing both the decision of when a speaker begins or ends an utterance and the interactions involved in that decision. turn-taking mechanisms are essential for achieving natural dialogue in both human-human and human-dialogue system communication @xcite @xcite . traditional research on turn-taking has provided valuable insights into the factors (e.g., linguistic and non-linguistic cues) that prompt turn transitions and the mechanisms underlying them @xcite @xcite . building on these findings, research on turn-taking models has progressed significantly; however, discussions have primarily focused on the binary decision of whether to take a turn @xcite . consequently, many dialogue systems implement turn-taking with fixed speeds, lacking the flexibility to adapt to varying conversational contexts and individual speaker characteristics. in practice, turn-taking speed-the timing of turn exchanges-carries important communicative meaning. for example, a quick response may convey active engagement, while a delayed response can indicate thoughtfulness or reflection. these timing behaviors are employed both consciously and unconsciously in human-human interactions. however, discussions focusing solely on the decision to take a turn overlook these context-sensitive and speaker-dependent adjustments. although few studies have focused specifically on turn-taking speed, cross-linguistic and cultural differences have been noted, with japanese exhibiting a distinctive distribution compared to other languages @xcite . furthermore, individual variation and situational factors-such as conversational topic, emotional intensity, and social dynamics-highlight the need for adaptive control of turn-taking speed @xcite . to address this gap, we conducts both empiri-cal analysis and predictive modeling of turn-taking speed based on various speaker characteristics. figure 1 provides a conceptual overview of turn-taking speed in conversation. first, we analyze how turn-taking speed varies with speaker role (expert vs. novice), interpersonal relationship (friend vs. stranger), and big five personality traits (openness, agreeableness, conscientiousness, and neuroticism). building on prior work modeling human's turn taking speed with gamma distributions @xcite , we then develop a predictive model whose mean and variance parameters are conditioned on these speaker characteristics. experimental results demonstrate that the proposed model more accurately reflects individual differences in turn-taking speed under varied conversational conditions. our contributions are summarized as follows: ## related work in this section, we review previous studies on turntaking and the influence of individual personality traits on role allocation and speaking behavior in dialogue. ## experimental design in this study, we analyze a corpus of human-tohuman dialogue to investigate the various factors that influence turn-taking speed. the source code used in the experiments is publicly available foot_0 . the details of the experiment are described below. ## discussion the results of this study suggest that turn-taking speed varies significantly depending on the roles, relationships, and personality of the dialogue participants. this indicates that the timing of utterances in dialogue is strongly influenced not only by linguistic factors but also by psychological and social factors. ## limitations and future work despite the novel insights provided by this study, several limitations should be noted, and directions for future work are identified. ## conclusion in this study, we investigated how turn-taking speed varies in human-human dialogue and demonstrated its dependence on speaker role (expert vs. novice), interpersonal relationship (friends vs. strangers), and big five personality traits. our empirical analysis revealed clear associations between these factors and both the shape and scale parameters of turn-taking intervals. building on these findings, we developed a threeparameter gamma distribution-based predictive model whose parameters are conditioned on subgroup mean and variance. this simple adjustment method reduced the kolmogorov-smirnov statistic and achieved hellinger similarities at max 99. 20%, confirming its high fidelity in reproducing observed speed distributions. overall, our approach lays the groundwork for adaptive turn-taking strategies in dialogue systems. by dynamically modulating response timing according to user characteristics, future conversa-tional agents and human-robot interfaces can deliver more natural, context-aware interactions.