Rockit

Renals, Steve; Carletta, Jean; Edwards, Keith; Bourlard, Hervé; Garner, Phil; Popescu-Belis, Andréi; Klakow, Dietrich; Girenko, Andrey; Petukova, Volha; Wacker, Philippe; Joscelyne, Andrew; Kompis, Costis; Aliwell, S; Stevens, William F.; Sabbah, Youssef

doi:10.1145/2666253.2666262

Cited by 3 publications

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Computing Technologies for Social Signals

Vinciarelli

2016

Human–Computer Interaction Series

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Personalized systems aim at adapting the content, the interface or the services in general to each user. As an integral part of our daily interactions on the web in various forms, from search engines to online shopping websites, they help us find contents more efficiently. The technologies that drive the adaptation to end users are based on the inference of user's preferences and characteristics from the traces that the user leaves while interacting with the applications. Traditionally, explicit and implicit user feedback has been used to model the users.Personalized services can now take advantage of more detailed user profiles that include highly descriptive features, such as emotions and personality. This has become possible with the advent of robust methods for an unobtrusive detection of personality, emotions and sentiments from different modalities, such as social media traces, mobile devices and sensors.This book brings in a single volume the basic bricks needed to understand and build personalized systems based on emotions and personality along with more advanced topics. It bridges personalization algorithms, such as recommender systems, with psychologically motivated user-centric concepts, such as emotions and personality. It translates psychological theories of emotions and personality into computational models for use in personalization algorithms. It surveys techniques for the implicit and explicit acquisition of personality, emotions, sentiments and social signals from sensors, mobile devices and social media. It provides design hints to develop emotion-and personality-aware systems as well as examples of personalized applications that make good use of personality. This book will help researchers and practitioners develop and evaluate user-centric personalization systems that take into account the factors that have a tremendous impact on our decision-making emotions and personality.In the first part of the book, the theoretical background for the psychological constructs of emotions and personality is given. The second part covers the state-of-the-art methods for the unobtrusive acquisitions of emotions, personality, social signals and sentiments. The third part describes the concrete applications of personalized systems working in a wide range of domains (from music vii

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Computing Technologies for Social Signals

Vinciarelli

2016

Human–Computer Interaction Series

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

et al. 2015

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Modeling, analysis and synthesis of behaviour are the subject of major efforts in computing science, especially when it comes to technologies that make sense of humanhuman 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 of the focus of interest from individuals to dyads and groups, 3) endowment of artificial agents with internal representations of users and context, 4) modeling of cognitive and semantic processes underlying social behaviour, and 5) identification of application domains and strategies for moving from laboratory to the realworld products.

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Towards conversational technology to promote, monitor and protect mental health

Callejas¹,

Griol²,

Benghazi³

et al. 2021

IberSPEECH 2021

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This paper presents a general overview of the H2020-MSCA-RISE project MENHIR (Mental health monitoring through interactive conversations), which aim is to explore the possibilities of conversational technologies (chatbots) to understand, promote and protect mental health and assist people with anxiety and mild depression manage their conditions. MENHIR started on February 2019 and will have a duration of 4 years. Its consortium brings together 8 partners including universities, a non-profit organization and companies.

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Rockit

Cited by 3 publications

References 1 publication

Computing Technologies for Social Signals

Computing Technologies for Social Signals

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

Towards conversational technology to promote, monitor and protect mental health

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