How do speakers coordinate? Evidence for prediction in a joint word-replacement task

Visual memory of a co-actor's target during joint search

Studies on joint action show that when two actors turn-takingly attend to each other's target that appears one at a time, a partner's target is accumulated in memory. However, in the real world, actors may not be certain that they attend to the same object because multiple objects often appear simultaneously. In this study, we asked participant pairs to search for different targets in parallel from multiple objects and investigated the memory of a partner's target. We employed the contextual cueing paradigm, in which repetitive search forms associative memory between a target and a configuration of distractors that facilitates search. During the learning phase, exemplars of three target categories (i.e., bird, shoe, and tricycle) were presented among unique objects, and participant pairs searched for them. In Experiment 1, it was followed by a memory test about target exemplars. Consequently, the partner's target was better recognized than the target that nobody searched for. In Experiments 2a and 2b, the memory test was replaced with the transfer phase, where one individual from the pair searched for the category that nobody had searched for while the other individual searched for the category the partner had searched for in the learning phase. The transfer phase did not show search facilitation underpinned by associative memory between the partner's target and distractors. These results suggest that when participant pairs search for different targets in parallel, they accumulate the partner's target in memory but may not form its associative memory with the distractors that facilitates its search.

Interference in the shared-Stroop task: a comparison of self- and other-monitoring

Co-actors represent and integrate each other's actions, even when they need not monitor one another. However, monitoring is important for successful interactions, particularly those involving language, and monitoring others' utterances probably relies on similar mechanisms as monitoring one's own. We investigated the effect of monitoring on the integration of self- and other-generated utterances in the shared-Stroop task. In a solo version of the Stroop task (with a single participant responding to all stimuli; Experiment 1), participants named the ink colour of mismatching colour words (incongruent stimuli) more slowly than matching colour words (congruent). In the shared-Stroop task, one participant named the ink colour of words in one colour (e.g. red), while ignoring stimuli in the other colour (e.g. green); the other participant either named the other ink colour or did not respond. Crucially, participants either provided feedback about the correctness of their partner's response (Experiment 3) or did not (Experiment 2). Interference was greater when both participants responded than when they did not, but only when their partners provided feedback. We argue that feedback increased interference because monitoring one's partner enhanced representations of the partner's target utterance, which in turn interfered with self-monitoring of the participant's own utterance.

Towards a New Model of Verbal Monitoring

As all human activities, verbal communication is fraught with errors. It is estimated that humans produce around 16,000 words per day, but the word that is selected for production is not always correct and neither is the articulation always flawless. However, to facilitate communication, it is important to limit the number of errors. This is accomplished via the verbal monitoring mechanism. A body of research over the last century has uncovered a number of properties of the mechanisms at work during verbal monitoring. Over a dozen routes for verbal monitoring have been postulated. However, to date a complete account of verbal monitoring does not exist. In the current paper we first outline the properties of verbal monitoring that have been empirically demonstrated. This is followed by a discussion of current verbal monitoring models: the perceptual loop theory, conflict monitoring, the hierarchical state feedback control model, and the forward model theory. Each of these models is evaluated given empirical findings and theoretical considerations. We then outline lacunae of current theories, which we address with a proposal for a new model of verbal monitoring for production and perception, based on conflict monitoring models. Additionally, this novel model suggests a mechanism of how a detected error leads to a correction. The error resolution mechanism proposed in our new model is then tested in a computational model. Finally, we outline the advances and predictions of the model.

Initiation of utterance planning in response to pre-recorded and "live" utterances

In everyday conversation, interlocutors often plan their utterances while listening to their conversational partners, thereby achieving short gaps between their turns. Important issues for current psycholinguistics are how interlocutors distribute their attention between listening and speech planning and how speech planning is timed relative to listening. Laboratory studies addressing these issues have used a variety of paradigms, some of which have involved using recorded speech to which participants responded, whereas others have involved interactions with confederates. This study investigated how this variation in the speech input affected the participants' timing of speech planning. In Experiment 1, participants responded to utterances produced by a confederate, who sat next to them and looked at the same screen. In Experiment 2, they responded to recorded utterances of the same confederate. Analyses of the participants' speech, their eye movements, and their performance in a concurrent tapping task showed that, compared with recorded speech, the presence of the confederate increased the processing load for the participants, but did not alter their global sentence planning strategy. These results have implications for the design of psycholinguistic experiments and theories of listening and speaking in dyadic settings.

Monitoring speech production and comprehension: Where is the second-language delay?

Research on error monitoring suggests that bilingual Dutch-English speakers are slower to correct some speech errors in their second language (L2) as opposed to their first language (L1). But which component of self-monitoring is slowed down in L2, error detection or interruption and repair of the error? This study charted the time course of monitoring in monolingual English speakers and bilingual Dutch-English speakers in language production and language comprehension, with the aim of pinpointing the component(s) of monitoring that cause an L2 disadvantage. First, we asked whether phonological errors are interrupted more slowly in L2. An analysis of data from three speech error elicitation experiments indeed showed that Dutch-English bilinguals were slower to stop speaking after an error had been detected in their L2 (English) than in their L1 (Dutch), at least for interrupted errors. A similar L2 disadvantage was found when comparing the L2 of Dutch-English bilinguals to the L1 of English monolinguals. Second, monolingual English speakers and bilingual Dutch-English speakers performed a picture naming task, a production monitoring task, and a comprehension monitoring task. Bilingual English speakers were slower in naming pictures in their L2 than monolingual English speakers. However, the production monitoring task and comprehension monitoring task yielded comparable response latencies between monolinguals in their L1 and bilinguals in their L2, indicating that monitoring processes in L2 are not generally slower. We suggest that interruption and repair are planned concurrently and that the difficulty of repairing in L2 triggers a slow-down in L2 interruption.

Working Together: Contributions of Corpus Analyses and Experimental Psycholinguistics to Understanding Conversation

As conversation is the most important way of using language, linguists and psychologists should combine forces to investigate how interlocutors deal with the cognitive demands arising during conversation. Linguistic analyses of corpora of conversation are needed to understand the structure of conversations, and experimental work is indispensable for understanding the underlying cognitive processes. We argue that joint consideration of corpus and experimental data is most informative when the utterances elicited in a lab experiment match those extracted from a corpus in relevant ways. This requirement to compare like with like seems obvious but is not trivial to achieve. To illustrate this approach, we report two experiments where responses to polar (yes/no) questions were elicited in the lab and the response latencies were compared to gaps between polar questions and answers in a corpus of conversational speech. We found, as expected, that responses were given faster when they were easy to plan and planning could be initiated earlier than when they were harder to plan and planning was initiated later. Overall, in all but one condition, the latencies were longer than one would expect based on the analyses of corpus data. We discuss the implication of this partial match between the data sets and more generally how corpus and experimental data can best be combined in studies of conversation.

Encouraging prediction during production facilitates subsequent comprehension: Evidence from interleaved object naming in sentence context and sentence reading

Many studies have shown that a supportive context facilitates language comprehension. A currently influential view is that language production may support prediction in language comprehension. Experimental evidence for this, however, is relatively sparse. Here we explored whether encouraging prediction in a language production task encourages the use of predictive contexts in an interleaved comprehension task. In Experiment 1a, participants listened to the first part of a sentence and provided the final word by naming aloud a picture. The picture name was predictable or not predictable from the sentence context. Pictures were named faster when they could be predicted than when this was not the case. In Experiment 1b the same sentences, augmented by a final spill-over region, were presented in a self-paced reading task. No difference in reading times for predictive versus non-predictive sentences was found. In Experiment 2, reading and naming trials were intermixed. In the naming task, the advantage for predictable picture names was replicated. More importantly, now reading times for the spill-over region were considerable faster for predictive than for non-predictive sentences. We conjecture that these findings fit best with the notion that prediction in the service of language production encourages the use of predictive contexts in comprehension. Further research is required to identify the exact mechanisms by which production exerts its influence on comprehension.