The development of predictive processes in children’s discourse understanding

The development of predictive processes in children’s discourse understanding Marisa Casillas Michael C. Frank middyp@stanford.edu Department of Linguistics Stanford University mcfrank@stanford.edu Department of Psychology Stanford University Abstract what linguistic material will follow (e.g., Altmann & Kamide, 1999; Ito & Speer, 2008; Snedeker & Yuan, 2008). In multi-utterance contexts, like conversation, speakers must also coordinate their ongoing actions, and so our pre- dictive prowess is even more to our advantage than it is in the lab. There is both naturally-occurring and experimental evidence that adults effortlessly anticipate when a speaker switch will occur during conversation. In order to respond with brief gaps, they need to accurately predict when to be- gin speaking (Sacks et al., 1974). There is also experimental evidence that adults can anticipate upcoming turn-structure— when asked to press a button when they think a speaker will finish her turn, adult listeners demonstrate incredible timing accuracy (M = 168 ms from the offset of speech; de Ruiter et al., 2006). They also spontaneously track turn-timing and anticipate upcoming speakers with their gaze when watching videos of conversation (Tice & Henetz, 2011). Here we ask: do children also make online predictions about conversation? We focus on how children process the multi-utterance speech around them because, as mentioned, children’s conversational skill and experience can influence their later language learning. Children learn language in the context of conversation, and their conversational skills allow them to practice com- prehending and using language with others. Children be- gin to take turns in early infancy, but their coordination of turn-timing with others takes several years to develop. By four months, infants regularly engage in coordinated back- and-forth interactions with their caregivers (Masataka, 1993). Twelve-month-old infants who are watching two-person con- versations can (1) track who is speaking, and (2) expect speech to be responded to verbally (Thorgr´imsson et al., 2011). Despite this, even at 5;0, children’s timing is signifi- cantly delayed compared to adults’—their response delay at 3;0 is up to 10 times slower (Casillas et al., in prep)—leading some to believe that children can’t or don’t perform the same predictive processing that adults do (Garvey & Berninger, We propose that, on the contrary, children develop their predictive turn-taking skill early in life, and that their ap- parent delay is due to the time needed to plan and execute a response. Thus, when children simply observe an ongo- ing interaction, they show predictive timing similar to adult norms. Casillas and Frank (2012) found that when children and adults watched videos of conversation in a language they didn’t speak, they were able to use the available information We investigate children’s online predictive processing as it oc- curs naturally, in conversation. We showed 1–7 year-olds short videos of improvised conversation between puppets, control- ling for available linguistic information through phonetic ma- nipulation. Even one- and two-year-old children made ac- curate and spontaneous predictions about when a turn-switch would occur: they gazed at the upcoming speaker before they heard a response begin. This predictive skill relies on both lex- ical and prosodic information together, and is not tied to either type of information alone. We suggest that children integrate prosodic, lexical, and visual information to effectively predict upcoming linguistic material in conversation. Keywords: Prediction; online comprehension; turn-taking; timing; child language; prosody; eye-tracking Introduction Conversation is the primary way we use language. It is most often spoken face-to-face with two or more speakers, and is deeply embedded in our current interactional context. Partic- ipants in conversation don’t just listen; given that inter-turn gaps are so brief, speakers must be simultaneously planning at least part of their response while the current speaker is still talking (Sacks et al., 1974; Stivers et al., 2009). So under normal conditions, listeners deal with critically different pro- cessing pressures during conversation than they do in rigidly controlled experiments. For children especially, experience and skill in processing and conversation can be critical to later language development (e.g., Weisleder, 2012). The current study seeks to draw a link between language processing in the lab and language processing in broader contexts by trac- ing predictive processing during conversation across a broad developmental sample. Timing is critical in conversation because, in addition to parsing the linguistic signal for its parts and meanings, con- versational participants are interested in the upkeep of the on- going interaction. For example, if someone asks you, “What are your plans for dinner?” you are obligated to do more than just parse the linguistic signal; you must respond. You can’t just respond at your convenience either—especially for an implied invitation like this one, a slight hesitation might communicate that you will turn the offer down. This is a sub- stantial cognitive load to bear since speakers must quickly figure out what was said and how to respond. Predictive pro- cesses can help maintain the flow of conversation by allowing us to plan for what is likely to happen next in the interaction. When listening to a single utterance, we make predictions about what the speaker will say next. Many studies have shown that we can use a wide variety of linguistic and non- linguistic cues to incrementally update our expectations about 1 Cf. Snedeker & Yuan, 2008 for more on children’s sentence processing.