Marisa Casillas

Editorial: Turn-Taking in Human Communicative Interaction

One intriguing feature of the human communication system is the interactional infrastructure it builds on. In both dyadic and multi-person interactions, conversation is highly structured and organized according to set principles (Sacks et al., 1974). Human adult interaction is characterized by a mechanism of exchange based on alternating (and relatively short) bursts of information. In the majority of cases, only one person tends to speak at a time and each contribution usually receives a response. What is remarkable is the precise timing of these sequential contributions, resulting in gaps between speaking turns averaging around just 200 ms (Stivers et al., 2009). From psycholinguistic experiments, we know that the time it takes to produce even simple one-word-utterances (min. 600 ms, Indefrey and Levelt, 2004) by far exceeds this average gap duration, hinting at the complexity of the cognitive processes that must be involved (Levinson, 2013). While the behavioral principles governing turn-taking in interaction have been researched for some decades—primarily by scholars of conversation analysis—the cognitive underpinnings of the human turn-taking system have long remained elusive. Recently, psycholinguists have begun to explore the cognitive and neural processes that allow us to deal effectively with the immensely complex task of taking turns on time. Amongst other things, this has highlighted the anticipatory, predictive processes that must be at work, as well as the different layers of processing allowing production planning and comprehension to take place simultaneously (de Ruiter et al., 2006; Magyari and de Ruiter; Bogels et al., 2015). These insights mesh well with the conversation analytic literature that has illuminated the interactional environments in which individual turns are embedded: their sequential organization and the use of conventionalized linguistic constructions allow for the projection of upcoming talk, as well as for the recognition of points of possible completions in the turn which make transition to the next speaker relevant (Sacks et al., 1974; Ford and Thompson, 1996; Schegloff, 2007). The articles in this Research Topic bring together these as yet largely independent lines of research to elucidate our understanding of turn-taking from multiple perspectives and aim to foster future synergies. In addition to exploring the adult psycholinguistic machinery and its workings, researchers have begun to wonder how and when the required cognitive and social processes mature in children, as well as how they compare to those in other species. Levinson (2006) proposed that human beings are inherently social and interactive in orientation. He argues that an “interaction engine” may lie at the heart of childrens early predisposition for turn-taking. Likewise, this particular human capacity might explain the strong cultural universals in the structure of human interaction as well as the striking commonalities and differences in communication systems brought about by the course of evolution. The present Research Topic provides a collection of experimental and observational empirical studies using qualitative and quantitative approaches, complemented by articles offering reviews, opinions, and models. They aim to inform the reader about the most recent advances in our endeavor of unraveling the workings of the human turn-taking system in communicative interaction. The contributions are organized into six sections: (1) Foundations of turn-taking, (2) Signals and mechanisms for prediction and timing, (3) Planning next turns in conversation, (4) Effects of context and function on timing, (5) Turn-taking in signed languages, and (6) Development of turn-taking skills.

Turn-Taking in Human Communicative Interaction

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What Do North American Babies Hear? A large-scale cross-corpus analysis

A range of demographic variables influences how much speech young children hear. However, because studies have used vastly different sampling methods, quantitative comparison of interlocking demographic effects has been nearly impossible, across or within studies. We harnessed a unique collection of existing naturalistic, day-long recordings from 61 homes across four North American cities to examine language input as a function of age, gender, and maternal education. We analyzed adult speech heard by 3- to 20-month-olds who wore audio recorders for an entire day. We annotated speaker gender and speech register (child-directed or adult-directed) for 10,861 utterances from female and male adults in these recordings. Examining age, gender, and maternal education collectively in this ecologically valid dataset, we find several key results. First, the speaker gender imbalance in the input is striking: children heard 2-3× more speech from females than males. Second, children in higher-maternal education homes heard more child-directed speech than those in lower-maternal education homes. Finally, our analyses revealed a previously unreported effect: the proportion of child-directed speech in the input increases with age, due to a decrease in adult-directed speech with age. This large-scale analysis is an important step forward in collectively examining demographic variables that influence early development, made possible by pooled, comparable, day-long recordings of childrens language environments. The audio recordings, annotations, and annotation software are readily available for reuse and reanalysis by other researchers.

Predictive processing during discourse comprehension

We investigate childrens online predictive processing as it occurs naturally, in conversation. We showed 129 children (1;0–7;0) short videos of improvised conversation between puppets, controlling for available linguistic information through phonetic manipulation: normal, prosody only (low-pass filtered), lexical only (rhythm controlled and pitch flattened), and none (multi-talker babble). We tracked their eye movements during the videos, measuring their anticipatory looks to upcoming speakers at points of turn switch (e.g., after a question and before an answer). Even one- and two-year-old children made accurate and spontaneous predictions about when a turn-switch would occur: they gazed at the upcoming speaker before they heard a response begin. By age three, children distinguished between different types of response-eliciting speech acts, looking faster to question- than non-question responses—but only when all linguistic information was available. By age seven, children’s gaze behavior also distingui...

The Meet a Friend corpus of spontaneous speech: New data, initial results

We introduce a new collection of 60 spontaneous speech recordings that we are making available to the wider linguistic community. We video and audio recorded sixty pairs of American English speakers as they talked freely for 20 min about four general topics (e.g., pets, food, movies). Half of the pairs came in as friends, half as strangers. The corpus contains one third each of female-female, female-male, and male-male speaker pairs. Before the recording, each participant completed a Ten Item Personality (TIPI) assessment. Afterwards, each participant gave a review of their and their partner’s behavior during the conversation. Each recording is then transcribed in three passes by separate transcribers and applied to the audio recording using the Penn Phonetics Lab Forced Aligner for extended search and automated extraction abilities. We present a few initial results using these new data. For example, by extracting turn-switch gaps and comparing them to participant ratings, we find support from these naturalistic data for prior, controlled experimental work showing that inter-turn gap times relate to social evaluations of the ongoing interaction. We compare disfluency between friend- and stranger-pairs, linking these patterns to any disfluency accommodation that occurred during the interaction.