{"title":"理解对话:语言使用和社会互动","authors":"Rachel Bawden","doi":"10.1162/coli_r_00411","DOIUrl":null,"url":null,"abstract":"Understanding Dialogue: Language Use and Social Interaction represents a departure from classic theories in psycholinguistics and cognitive sciences; instead of taking as a starting point the isolated speech of an individual that can be extended to accommodate dialogue, a primary focus is put on developing a model adapted to dialogue itself, bearing in mind important aspects of dialogue as an activity with a heavily cooperative component. As a researcher of natural language processing with a background in linguistics, I find highly intriguing the possibilities provided by the dialogue model presented. Although the book does not itself touch upon the potential for automated dialogue, I am inevitably writing this review from the point of view of a computational linguist with these aspects in mind. Building on numerous previous works, including many of the authors’ own studies and theories, Understanding Dialogue presents the shared workspace framework, a framework for understanding not just dialogue but cooperative activities in general, of which dialogue is viewed as a subtype. Based on Bratman’s (1992) concept of shared cooperative activity, the framework provides a joint environment with which interlocutors can interact, both by contributing to the space (with actions or utterances for example), and by perceiving and processing their own or the other participants’ productions. The authors do not limit their work to linguistic communication: Many of their examples, particularly at the beginning of the book, are non-linguistic (e.g., hand shaking, dancing a tango, playing singles tennis); others are primarily physical, but will most likely also involve linguistic communication (such as jointly constructing flat-pack furniture); and others are purely linguistic (e.g., suggesting which restaurant to go to for lunch). The notion of alignment is highly important to this framework both from a linguistic and non-linguistic perspective, and is one of the main inspirations of the book, having previously been presented in Toward a Mechanistic Theory of Dialogue by the same authors. As individuals interact via the joint space, alignment concerns the equivalence in their representations at a conceptual level, with respect to their goals and relevant props in the shared environment (dialogue model alignment) and linguistic representations shared in the workspace (linguistic alignment). Roughly speaking, in this second (linguistic) case, this may for instance correspond to whether or not the individuals have the same representation of the utterance in terms of phonetics (were the sounds perceived correctly?) or in terms of lexical semantics (do they understand the same reference by the word uttered?). 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As a researcher of natural language processing with a background in linguistics, I find highly intriguing the possibilities provided by the dialogue model presented. Although the book does not itself touch upon the potential for automated dialogue, I am inevitably writing this review from the point of view of a computational linguist with these aspects in mind. Building on numerous previous works, including many of the authors’ own studies and theories, Understanding Dialogue presents the shared workspace framework, a framework for understanding not just dialogue but cooperative activities in general, of which dialogue is viewed as a subtype. Based on Bratman’s (1992) concept of shared cooperative activity, the framework provides a joint environment with which interlocutors can interact, both by contributing to the space (with actions or utterances for example), and by perceiving and processing their own or the other participants’ productions. The authors do not limit their work to linguistic communication: Many of their examples, particularly at the beginning of the book, are non-linguistic (e.g., hand shaking, dancing a tango, playing singles tennis); others are primarily physical, but will most likely also involve linguistic communication (such as jointly constructing flat-pack furniture); and others are purely linguistic (e.g., suggesting which restaurant to go to for lunch). The notion of alignment is highly important to this framework both from a linguistic and non-linguistic perspective, and is one of the main inspirations of the book, having previously been presented in Toward a Mechanistic Theory of Dialogue by the same authors. As individuals interact via the joint space, alignment concerns the equivalence in their representations at a conceptual level, with respect to their goals and relevant props in the shared environment (dialogue model alignment) and linguistic representations shared in the workspace (linguistic alignment). Roughly speaking, in this second (linguistic) case, this may for instance correspond to whether or not the individuals have the same representation of the utterance in terms of phonetics (were the sounds perceived correctly?) or in terms of lexical semantics (do they understand the same reference by the word uttered?). 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Understanding Dialogue: Language Use and Social Interaction
Understanding Dialogue: Language Use and Social Interaction represents a departure from classic theories in psycholinguistics and cognitive sciences; instead of taking as a starting point the isolated speech of an individual that can be extended to accommodate dialogue, a primary focus is put on developing a model adapted to dialogue itself, bearing in mind important aspects of dialogue as an activity with a heavily cooperative component. As a researcher of natural language processing with a background in linguistics, I find highly intriguing the possibilities provided by the dialogue model presented. Although the book does not itself touch upon the potential for automated dialogue, I am inevitably writing this review from the point of view of a computational linguist with these aspects in mind. Building on numerous previous works, including many of the authors’ own studies and theories, Understanding Dialogue presents the shared workspace framework, a framework for understanding not just dialogue but cooperative activities in general, of which dialogue is viewed as a subtype. Based on Bratman’s (1992) concept of shared cooperative activity, the framework provides a joint environment with which interlocutors can interact, both by contributing to the space (with actions or utterances for example), and by perceiving and processing their own or the other participants’ productions. The authors do not limit their work to linguistic communication: Many of their examples, particularly at the beginning of the book, are non-linguistic (e.g., hand shaking, dancing a tango, playing singles tennis); others are primarily physical, but will most likely also involve linguistic communication (such as jointly constructing flat-pack furniture); and others are purely linguistic (e.g., suggesting which restaurant to go to for lunch). The notion of alignment is highly important to this framework both from a linguistic and non-linguistic perspective, and is one of the main inspirations of the book, having previously been presented in Toward a Mechanistic Theory of Dialogue by the same authors. As individuals interact via the joint space, alignment concerns the equivalence in their representations at a conceptual level, with respect to their goals and relevant props in the shared environment (dialogue model alignment) and linguistic representations shared in the workspace (linguistic alignment). Roughly speaking, in this second (linguistic) case, this may for instance correspond to whether or not the individuals have the same representation of the utterance in terms of phonetics (were the sounds perceived correctly?) or in terms of lexical semantics (do they understand the same reference by the word uttered?). From here can be explained a number of different dialogue
期刊介绍:
Computational Linguistics, the longest-running publication dedicated solely to the computational and mathematical aspects of language and the design of natural language processing systems, provides university and industry linguists, computational linguists, AI and machine learning researchers, cognitive scientists, speech specialists, and philosophers with the latest insights into the computational aspects of language research.