Language use is inherently social; discourse and dialogue unfold in social contexts. This chapter presents an introduction to the cognitive science of discourse and dialogue, from an interdisciplinary perspective that includes experimental psycholinguistics, sociolinguistics, artificial intelligence, human–machine interaction, and neuroscience. Two dominant experimental traditions, language‐as‐product and language‐as‐action, are discussed, and some classic issues, findings, and theories in discourse processing are presented. Topics surveyed include information packaging, referential communication, achieving joint meanings in dialogue, models of discourse and dialogue structure, audience design and partner‐specific processing, and the neural bases of discourse and dialogue. Evidence from experiments and examples from communicative contexts are presented that shed light on how people plan, interpret, and coordinate language within dialogue. The research presented here holds implications for writing for better comprehension, improving robustness in human interaction with spoken dialogue systems, and understanding the neural processing of language during communication.
In conversational speech, it is very common for words' segments to be reduced or deleted. However, previous research has consistently shown that during spoken word recognition, listeners prefer words' canonical pronunciation over their reduced pronunciations (e.g., pretty pronounced [prɪti] vs. [prɪɾi]), even when the latter are far more frequent. This surprising effect violates most current accounts of spoken word recognition. The current study tests the possibility that words' orthography may be one factor driving the advantage for canonical pronunciations during spoken word recognition. Participants learned new words presented in their reduced pronunciation (e.g. [trɒti]), paired with one of three spelling possibilities: (1) no accompanying spelling, (2) a spelling consistent with the reduced pronunciation (a reduced spelling, e.g., "troddy"), or (3) a spelling consistent with the canonical pronunciation (a canonical spelling, e.g., "trotty"). When listeners were presented with the new words' canonical forms for the first time, they erroneously accepted them at a higher rate if the words had been learned with a canonical spelling. These results remained robust after a delay period of 48 hours, and after additional learning trials. Our findings suggest that orthography plays an important role in the recognition of spoken words and that it is a significant factor driving the canonical pronunciation advantage observed previously.
The speech perception system adjusts its phoneme categories based on the current speech input and lexical context. This is known as lexically driven perceptual recalibration , and it is often assumed to underlie accommodation to non-native accented speech. However, recalibration studies have focused on maximally ambiguous sounds (e.g., a sound ambiguous between “sh” and “s” in a word like “superpower”), a scenario that does not represent the full range of variation present in accented speech. Indeed, non-native speakers sometimes completely substitute a phoneme for another, rather than produce an ambiguous segment (e.g., saying “ sh uperpower”). This has been called a “bad map” in the literature. In this study, we scale up the lexically driven recalibration paradigm to such cases. Because previous research suggests that the position of the critically accented phoneme modulates the success of recalibration, we include such a manipulation in our study. And to ensure that participants treat all critical items as words (an important point for successful recalibration), we use a new exposure task that incentivizes them to do so. Our findings suggest that while recalibration is most robust after exposure to ambiguous sounds, it also occurs after exposure to bad maps. But interestingly, positional effects may be reversed: recalibration was more likely for ambiguous sounds late in words, but more likely for bad maps occurring early in words. Finally, a comparison of an online versus in-lab version of these conditions shows that experimental setting may have a non-trivial effect on the results of recalibration studies.
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