Turn-taking in children and adults: predictive or reactive? Laura Lindsay, Chiara Gambi, Martin Pickering, & Hugh Rabagliati Department of Psychology, University of Edinburgh BIG PICTURE: 3 QUESTIONS PREDICTION -> we can say something about timing (be clear it is only prediction of word length / not structure which was the same) EARLY PREPARATION  we can say they do for simple yes/no responses, but what about more complex responses? HOW DOES TURN TAKING DEVELOP?

The turn-taking puzzle During conversation, we take turns between speaking and listening: Short gaps/overlaps: 200 ms (Stivers et al., 2009) Production processes take time – at least 600ms for a single content word (Indefrey & Levelt, 2004) OVERLAPS GAPS Data from Stivers et al., 2009, PNAS

Three questions about turn-taking PREDICTION EARLY PREPARATION DEVELOPMENT Garrod and Pickering, 2015; Levinson 2016; see also De Ruiter et al., 2006; Magyari et al., 2014.

1. Prediction From 2;0, children make semantic predictions (Mani & Huettig, 2012) “cake” (CONTENT) ??400-600ms (TIMING) How can you not like birthdays !? Are you not excited at the idea of eating the … From 2;0, children observing a conversation look at the next speaker before she begins speaking (Casillas & Frank, 2012, Lammertink et al, 2015; see also: Keitel et al., 2013; Keitel & Daumm, 2015) Do children predict timing?

2. Early preparation Might be possible when: Speaker’s turn is predictable Listener’s turn is short and simple How can you not like birthdays !? Are you not excited at the idea of eating the … NO! However: children might struggle with early preparation because their planning abilities are slow to develop (Casillas and colleagues) Predicting content helps with response preparation, but if preparation occurs early enough then there is perhaps no need to predict timing. Bögels et al., 2015

3. The development of turn taking Corpus studies: 3 months to 18 months 1100 ms 700 ms MENTION ESTIMATES WHEN TALKING Depends on the complexity of the turn and its predictability based on the previous turn (Casillas et al., 2015; Garvey & Berninger, 1981) Note that Garvey and Berninger conclude that their data are consistent with reaction to turn-final cues without projection ala Sacks! Hilbrink et al., 2015 0;3 0;9 1;0 1;6 years; months 2;0 3;0

3. The development of turn taking Corpus studies: 2 to 3 and a half years 1100 ms 900 ms 700 ms 500 ms MENTION ESTIMATES WHEN TALKING Depends on the complexity of the turn and its predictability based on the previous turn (Casillas et al., 2015; Garvey & Berninger, 1981) Note that Garvey and Berninger conclude that their data are consistent with reaction to turn-final cues without projection ala Sacks! Hilbrink et al., 2015 Casillas et al., 2016 0;3 0;9 1;0 1;6 years; months 2;0 3;0

3. The development of turn taking Mother-child Child-child 1200 ms 800 ms (around 5;0) 1100 ms 900 ms 700 ms 500 ms MENTION ESTIMATES WHEN TALKING Depends on the complexity of the turn and its predictability based on the previous turn (Casillas et al., 2015; Garvey & Berninger, 1981) Note that Garvey and Berninger conclude that their data are consistent with reaction to turn-final cues without projection ala Sacks! Garvey and Berniger, 1981 Hilbrink et al., 2015 Casillas et al., 2016 0;3 0;9 1;0 1;6 years; months 2;0 3;0

3. The development of turn-taking Why does it take so long? Children’s production abilities take long to develop  early preparation is limited children predict semantics (CONTENT) and can prepare early, but they cannot not yet predict when the speaker’s turn is going to end (TIMING) Do children (and adults) predict when the speaker will stop talking by predicting what she is about to say?

This study Interactive iPad-based maze game (4 mazes) They guide a character around a maze. At decision points in the maze, the character asks participants what way he should go. Each direction was associated with a well-known children’s cartoon character. Children were familiarised with characters’ names at the start of each “level” in the game.

This study Example trial 24 adults Participants were reminded of the characters’ names before each maze They guide a character around a maze. At decision points in the maze, the character asks participants what way he should go. Each direction was associated with a well-known children’s cartoon character. Children were familiarised with characters’ names at the start of each “level” in the game. 24 adults 30 5-year-olds (one participant excluded, N=29) 47 3-year-olds (13 participants excluded, N=34)

Design Fully crossed, within-subjects: Answer Type Scene Type Is the content of the question (and its answer) predictable (YES answer) or not (NO answer)? Participants expect Peter Pan to ask about the correct direction (he is always right on filler items) Scene Type The game has 4 mazes, each with 36 trials (24 target trials and 12 filler trials)

Predictable Unpredictable Predictable Unpredictable Make clear that Predictable == YES, Unpredictable == NO answer ONLY USE RELEVANT LABELS

Predictable Unpredictable Predictable Unpredictable

Design Fully crossed, within-subjects: Answer Type Scene Type Is the content of the question predictable (YES answer) or not (NO answer)? Participants expect Peter Pan to ask about the correct direction (he is always right on filler items) Scene Type Are the names of the two characters the same length? MATCH: both short / long MISMATCH: one short / one long (mean difference: 430 ms)

Match Match Mismatch Mismatch ONLY USE RELEVANT LABELS

Match Match Mismatch Mismatch

Match Match Mismatch Mismatch Match, Predictable Match Match, Unpredictable Match Mismatch Mismatch, Predictable Mismatch Mismatch, Unpredictable Note that in DIFFERENT, UNPRED, they always expect a long one but hear a short one.

Hypotheses: gaps ANSWER TYPE: longer for unpredictable (NO answer) than predictable questions ANSWER TYPE * SCENE TYPE: if participants predict when the question will end by predicting its content; interaction: When the characters’ names mismatch in length, we should find a larger difference between predictable and unpredictable questions (compared to when the names match in length) Note that linguistic complexity of answer is controlled for

Hypotheses: gaps ANSWER TYPE: longer for unpredictable (NO answer) than predictable questions ANSWER TYPE * SCENE TYPE: if participants predict when the question will end by predicting its content; interaction: Note that linguistic complexity of answer is controlled for

Hypotheses: gaps ANSWER TYPE: longer for unpredictable (NO answer) than predictable questions ANSWER TYPE * SCENE TYPE: if participants predict when the question will end by predicting its content; interaction: Note that linguistic complexity of answer is controlled for

Hypotheses: gaps ANSWER TYPE: longer for unpredictable (NO answer) than predictable questions ANSWER TYPE * SCENE TYPE: if participants predict when the question will end by predicting its content; interaction: Decrease with age Adults < 5;0 < 3;0 Note that linguistic complexity of answer is controlled for

Results* - Answer Type All age groups take longer to respond to unpredictable (NO answer) than predictable questions (YES answer). 56 ms, t = 3.25 103 ms, t = 3.37 119 ms, t = 4.29 * Gaps < 2 sec; Linear mixed-effects models with maximal random structure; |t| > 2 means p<.05

Results* - Answer Type: Scene Type NO interaction between Answer Type and Scene Type in any age group. t = 0.58 t = 0.46 t =0.58 * Gaps < 2 sec ; Linear mixed-effects models with maximal random structure; |t| > 2 means p<.05

Results* – Early preparation (?) Exploratory analysis: is there evidence for early preparation? Character names varied in length If answer preparation starts before question end: Both adults’ and children’s response times were negatively correlated with the length of the character name – that is, the longer that character name, the faster the participants’ response Shorter gaps More preparation time Longer character names

Results* – Early preparation (?) Both adults’ and children’s response times were negatively correlated with the length of the character name – that is, the longer that character name, the faster the participants’ response The longer the character name, the faster the participant’s response * Gaps < 2 sec; by-item correlations

Results – Distributional Analysis Do children just get faster? Ex-gaussian distribution Three parameters: Mu (mean) Sigma (standard deviation) Tau (thickness of the tails) Tau = 100 Tau = 200 See Ratcliff, 1979

Results* Effect of Answer Type and lack of interaction Answer Type * Scene Type replicate on mu Children’s slow responding is driven by differences in the right tail of the distribution * Parameters jointly estimated with Bayesian linear regression

Predicting Timing? Neither children nor adults timed their answers to questions by predicting the length of the final word Predictions: “Fireman Sam” (CONTENT) 600-800ms (TIMING) Should we go past… Fireman Sam? Children and adults appear to behave similarly – neither predicts timing Do listeners predict question length/structure?

Early Response Preparation Instead, they rapidly prepared their answer as soon as possible, and responded reactively Predictions: “Po” (CONTENT) Should we go past… [p]? NO! Po is a short word, so there is less time to prepare a response NOTE: this study doesn’t directly test predictions about content – just an assumption LONG RESPONSE TIME

Early Response Preparation Instead, they rapidly prepared their answer as soon as possible, and responded reactively Predictions: “Fireman Sam” (CONTENT) Should we go past… [f]? YES! Fireman Sam is a long word, so there is more time to prepare a response SHORT RESPONSE TIME

How does the system develop? 3 yo and 5 yo leave longer gaps than adults However: Children are often as fast as adults Children are no more variable than adults Instead, children experience occasional “breakdowns”, leading to very long gaps.

Conclusion Children and adults were able to take turns quite rapidly without fine-grained timing prediction Early preparation of simple responses can afford reactive turn-taking strategies The building blocks of the turn-taking system are in place by age 3 Children leave long gaps, not because they are slow at producing answers, but because their turn-taking system is less stable

References Casillas, M., & Frank, M. C. (2013). The development of predictive processes in children’s discourse understanding. In CogSci 2013: The 35th annual meeting of the Cognitive Science Society (pp. 299-304). Cognitive Society. Casillas, M., & Frank, M. C. (2012). Cues to turn boundary prediction in adults and preschoolers. In SemDial 2012 (SeineDial) (pp. 61-69). Université Paris-Diderot. De Ruitter, J. P., Mitterer, H., Enfield, N. J., (2006). Projecting the end of a speaker’s turn: a cognitive cornerstone of conversation, Language, 82(3), 515-535 Garrod, S., & Pickering, M. J. (2015). The use of content and timing to predict turn transitions. Frontiers in psychology, 6. Lammertink, I., Casillas, M., Benders, T., Post, B., & Fikkert, P. (2015). Dutch and English toddlers' use of linguistic cues in predicting upcoming turn transitions. Frontiers in psychology, 6. Levinson, S. C., & Torreira, F. (2015). Timing in turn-taking and its implications for processing models of language. Frontiers in psychology, 6.

References Maygari, L. & De Ruitter, J. P., (2012). Prediction of turn-ends based on anticipation of upcoming words, Frontiers in Psychology, 3(376), 1-9 Magyari, L., Bastiaansen, M. C., de Ruiter, J. P., & Levinson, S. C. (2014). Early anticipation lies behind the speed of response in conversation. Journal of cognitive neuroscience, 26(11), 2530-2539. Riest, C., Jorschick, A. B., & De Ruiter, J. P. (2015). Anticipation in turn-taking: mechanisms and information sources. Frontiers in psychology, 6. Stivers, T., Enfield, N. J., Brown, P., Englert, C., Hayashi, M., Heinemann, T., ... & Levinson, S. C. (2009). Universals and cultural variation in turn-taking in conversation. Proceedings of the National Academy of Sciences, 106(26), 10587-10592.

The development of turn taking sensitivity to contingent vs. random exchanges (Bloom, et al. 1987) OVERLAPS 5% overlaps (Garvey & Berninger, 1981) decrease in overlaps: %40  %20 (Hilbrink et al., 2015) Maybe drop??? 0;3 0;9 1;0 1;6 2;0 3;0

The development of turn taking The duration of gaps varies hugely with the complexity of the response and its predictability 900 ms yes/no: 400-500 ms 500 ms Depends on the complexity of the turn and its predictability based on the previous turn (Casillas et al., 2015; Garvey & Berninger, 1981) Note that Garvey and Berninger conclude that their data are consistent with reaction to turn-final cues without projection ala Sacks! Casillas et al., 2016 0;3 0;9 1;0 1;6 2;0 3;0 see also Garvey & Berniger, 1981