Towards a Frame Semantics Lexical Resource for Greek

Proceedings of the Sixth International Workshop on Treebanks and Linguistic Theories. Editors: Koenraad De Smedt, Jan Hajič and Sandra Kübler. NEALT Proceedings Series, Vol. 1 (2007), 55-59. © 2007 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/4476

Open Challenges in Modelling, Analysis and Synthesis of Human Behaviour in Human--Human and Human--Machine Interactions

Modelling, analysis and synthesis of behaviour are the subject of major efforts in computing science, especially when it comes to technologies that make sense of human–human and human–machine interactions. This article outlines some of the most important issues that still need to be addressed to ensure substantial progress in the field, namely (1) development and adoption of virtuous data collection and sharing practices, (2) shift in the focus of interest from individuals to dyads and groups, (3) endowment of artificial agents with internal representations of users and context, (4) modelling of cognitive and semantic processes underlying social behaviour and (5) identification of application domains and strategies for moving from laboratory to the real-world products

Innovations in Big Data Mining and Embedded Knowledge

This chapter discusses the multimodal analysis of human behavioral data from the big data perspective. Though multimodal big data bring tremendous opportunities for related applications, we present current challenges in the domain of multimodal and behavioral analytics. We argue that in the case of analysing human behavior in interaction, we need to shift to the analysis of samples, smaller datasets, before scaling up to large data collections. We describe a dataset developed to study group collaborative interaction from measurable behavioral variables. As a case study, we investigate speech pauses and their patterns in the data, as well as their relationship to the topics of the dialog and the turn-taking mechanism, and we discuss their role in understanding the structure of collaborative interactions as well as in interpreting the behavior of the dialog participants

11th IEEE International Conference on Cognitive Infocommunications

We describe a heuristic-based approach to determining gaze allocation automatically in a multi-modal task oriented dialogue corpus. We present the development of the system and the evaluation of its performance and discuss the findings, including the shortcomings and the perspectives of the implemented approach

2020 IEEE International Conference on Human-Machine Systems (ICHMS)

We report on experiments in identifying personality traits from the dialogue of participants in the MULTISIMO corpus. Experiments used audio and linguistic features from participants? speech and transcripts, using both self- and ob-server personality reports. Contrary to our expectations that the linguistic content would best predict traits, the results highlight the multimodal nature of personality computing, suggesting that the content is less important than acoustics: except for two cases, models based on acoustic features only, or combined with linguistic features, outperform models based on linguistic features alone; results also show that there is no optimal choice of a single model or feature set for the prediction of a trait across personality reports, as different models work best for different traits

19th ACM International Conference on Multimodal Interaction (ICMI 2017)

This paper describes a recently created multimodal corpus that has been designed to address multiparty interaction modelling, specifically collaborative aspects in task-based group interactions. A set of human-human interactions was collected with HD cameras, microphones and a Kinect sensor. The scenario involves 2 participants playing a game instructed and guided by a facilitator. Additionally to the recordings, survey material was collected, including personality tests of the participants and experience assessment questionnaires. The corpus will be exploited for modelling behavioral aspects in collaborative group interaction by taking into account the speakers\u27 multimodal signals and psychological variables

11th IEEE International Conference on Cognitive Infocommunications

Observational methods in interaction analysis are defended. Observational methods are distinguished from experimental methods with respect to the mode of data collection.Other approaches to human interaction analysis considered are:prospective, technological, psychoanalytic and philosophical