A Hierarchical Ontology for Dialogue Acts in Psychiatric Interviews

2021 ◽  
Author(s):  
Aristeidis Bifis ◽  
Maria Trigka ◽  
Sofia Dedegkika ◽  
Panagiota Goula ◽  
Constantinos Constantinopoulos ◽  
...  
Keyword(s):  
Dialogue Acts

scholarly journals Types and annotation of reply relations in computer-mediated communication

2019 ◽  
Vol 7 (2) ◽  
pp. 305-332
Author(s):  
Laura Herzberg ◽  
Harald Lüngen
Keyword(s):  
Computer Mediated Communication ◽  
Mediated Communication ◽  
Dialogue Acts ◽  
Computer Mediated ◽  
Different Levels

AbstractThis paper presents types and annotation layers of reply relations in computer- mediated communication (CMC). Reply relations hold between post units in CMC interactions and describe references from one given post to a previous post. We classify three types of reply relations in CMC interactions: first, technical replies, i. e. the possibility to reply directly to a previous post by clicking a ‘reply’ button; second, indentations, e. g. in wiki talk pages in which users insert their contributions in the existing talk page by indenting them and third, interpretative reply relations, i. e. the reply action is not realised formally but signalled by other structural or linguistics means such as address markers ‘@’, greetings, citations and/or Q-A structures. We take a look at existing practices in the description and representation of such relations in corpora and examples of chat, Wikipedia talk pages, Twitter and blogs. We then provide an annotation proposal that combines the different levels of description and representation of reply relations and which adheres to the schemas and practices for encoding CMC corpus documents within the TEI framework as defined by the TEI CMC SIG. It constitutes a prerequisite for correctly identifying higher levels of interactional relations such as dialogue acts or discussion trees.

Prosody in Automatic Speech Processing

2020 ◽  
pp. 632-645
Author(s):  
Anton Batliner ◽  
Bernd Möbius
Keyword(s):  
Speech Processing ◽  
High Performance ◽  
Early Years ◽  
Short History ◽  
Word Level ◽  
Dialogue Acts ◽  
Semantics And Pragmatics ◽  
Different Types ◽  
History Of

Automatic speech processing (ASP) is understood as covering word recognition, the processing of higher linguistic components (syntax, semantics, and pragmatics), and the processing of computational paralinguistics (CP), which deals with speaker states and traits. This chapter attempts to track the role of prosody in ASP from the word level up to CP. A short history of the field from 1980 to 2020 distinguishes the early years (until 2000)—when the prosodic contribution to the modelling of linguistic phenomena, such as accents, boundaries, syntax, semantics, and dialogue acts, was the focus—from the later years, when the focus shifted to paralinguistics; prosody ceased to be visible. Different types of predictor variables are addressed, among them high-performance power features as well as leverage features, which can also be employed in teaching and therapy.

Dialogue

2014 ◽  
Author(s):  
Raquel Fernández
Keyword(s):  
Real Time ◽  
Computational Linguistics ◽  
Dynamic Semantic ◽  
Dialogue Acts ◽  
Turn Taking ◽  
Multi Agent ◽  
Conversational Language ◽  
Computational Research ◽  
New Challenges

Research on dialogue deals with the study of language as it is used in spontaneous conversation. Dialogue is a multi-agent activity that takes place in real time, with speakers interacting with each other in an online fashion. This makes conversational language markedly different from the kind of language found in texts and brings in new challenges for computational linguistics. This chapter introduces the main phenomena that characterize language in dialogue interaction—including disfluencies, dialogue acts, alignment, grounding, and turn taking—and discusses some of the key approaches to modelling dialogue that are fundamental in computational research, such as dialogue act taxonomies and dynamic semantic theories of dialogue.

scholarly journals Correlations between dialogue acts and learning in spoken tutoring dialogues

2006 ◽  
Vol 12 (2) ◽  
pp. 161-176 ◽  
Author(s):  
DIANE LITMAN ◽  
KATE FORBES-RILEY
Keyword(s):  
Student Learning ◽  
Adaptive Strategies ◽  
Promising Method ◽  
Student Dialogue ◽  
Dialogue Acts ◽  
Computer Tutoring

We examine correlations between dialogue behaviors and learning in tutoring, using two corpora of spoken tutoring dialogues: a human-human corpus and a human-computer corpus. To formalize the notion of dialogue behavior, we manually annotate our data using a tagset of student and tutor dialogue acts relative to the tutoring domain. A unigram analysis of our annotated data shows that student learning correlates both with the tutor's dialogue acts and with the student's dialogue acts. A bigram analysis shows that student learning also correlates with joint patterns of tutor and student dialogue acts. In particular, our human-computer results show that the presence of student utterances that display reasoning (whether correct or incorrect), as well as the presence of reasoning questions asked by the computer tutor, both positively correlate with learning. Our human-human results show that student introductions of a new concept into the dialogue positively correlates with learning, but student attempts at deeper reasoning (particularly when incorrect), and the human tutor's attempts to direct the dialogue, both negatively correlate with learning. These results suggest that while the use of dialogue act n-grams is a promising method for examining correlations between dialogue behavior and learning, specific findings can differ in human versus computer tutoring, with the latter better motivating adaptive strategies for implementation.

Computational Pragmatics

2016 ◽  
Author(s):  
Harry Bunt
Keyword(s):  
Recent Work ◽  
Language Use ◽  
Computational Tools ◽  
Use Of Resources ◽  
Corpus Construction ◽  
Dialogue Acts ◽  
Recent Developments ◽  
Dialogue Modeling ◽  
Context Of Use ◽  
Utterance Interpretation

This chapter presents a characterisation of the field of computational pragmatics, discusses some of the fundamental issues in the field, and provides a survey of recent developments. Central to computational pragmatics is the development and use of computational tools and models for studying the relations between utterances and their context of use. Essential for understanding these relations are the use of inference and the description of language use as actions inspired by the context, and intended to influence the context. The chapter therefore focuses on recent work in the use of inference for utterance interpretation and in dialogue modeling in terms of dialogue acts, viewed as context-changing actions. The chapter concludes with a survey of recent activities concerning the construction and use of resources in computational pragmatics, in particular annotation schemes, annotated corpora, and tools for corpus construction and use.

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