Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue

Research on human spoken language has shown that speech plays an important role in identifying speaker personality traits. In this work, we propose an approach for identifying speaker personality traits using overlap dynamics in multiparty spoken dialogues. We first define a set of novel features representing the overlap dynamics of each speaker. We then investigate the impact of speaker personality traits on these features using ANOVA tests. We find that features of overlap dynamics significantly vary for speakers with different levels of both Extraversion and Conscientiousness. Finally, we find that classifiers using only overlap dynamics features outperform random guessing in identifying Extraversion and Agreeableness, and that the improvements are statistically significant.Comment: Proceedings Interspeech 2019, Graz, Austria, Septembe

Using Hotspots as a Novel Method for Accessing Key Events in a Large Multi-Modal Corpus

n 2009 we created the D64 corpus, a multi-modal corpus which consists of roughly eight hours of natural, non-directed spontaneous interaction in an informal setting. Five participants feature in the recordings and their conversations were captured by microphones (room, body mounted and head mounted), video cameras and a motion capture system. The large amount of video, audio and motion capture material made it necessary to structure and make available the corpus in such a way that it is easy to browse and query for various types of data that we term primary, secondary and tertiary. While users are able to make simple and highly structured searches, we discuss the use of conversational hotspots as a method of searching the data for key events in the corpus; thus enabling a user to obtain a broad overview of the data. In this paper we present an approach to structuring and presenting a multi-modal corpus based on our experience with the D64 corpus that is accessible over the web, incorporates an interactive front-end and is open to all interested researchers and student

Speech & Multimodal Resources: the Herme Database of Spontaneous Multimodal Human-Robot Dialogues

This paper presents methodologies and tools for language resource (LR) construction. It describes a database of interactive speech collected over a three-month period at the Science Gallery in Dublin, where visitors could take part in a conversation with a robot. The system collected samples of informal, chatty dialogue – normally difficult to capture under laboratory conditions for human-human dialogue, and particularly so for human-machine interaction. The conversations were based on a script followed by the robot consisting largely of social chat with some task-based elements. The interactions were audio-visually recorded using several cameras together with microphones. As part of the conversation the participants were asked to sign a consent form giving permission to use their data for human-machine interaction research. The multimodal corpus will be made available to interested researchers and the technology developed during the three-month exhibition is being extended for use in education and assisted-living applications

Investigating Fine Temporal Dynamics of Prosodic and Lexical Accommodation

Conversational interaction is a dynamic activity in which participants engage in the construction of meaning and in establishing and maintaining social relationships. Lexical and prosodic accommodation have been observed in many studies as contributing importantly to these dimensions of social interaction. However, while previous works have considered accommodation mechanisms at global levels (for whole conversations, halves and thirds of conversations), this work investigates their evolution through repeated analysis at time intervals of increasing granularity to analyze the dynamics of alignment in a spoken language corpus. Results show that the levels of both prosodic and lexical accommodation fluctuate several times over the course of a conversation

An Empirical Study of Topic Transition in Dialogue

Transitioning between topics is a natural component of human-human dialog. Although topic transition has been studied in dialogue for decades, only a handful of corpora based studies have been performed to investigate the subtleties of topic transitions. Thus, this study annotates 215 conversations from the switchboard corpus and investigates how variables such as length, number of topic transitions, topic transitions share by participants and turns/topic are related. This work presents an empirical study on topic transition in switchboard corpus followed by modelling topic transition with a precision of 83% for in-domain(id) test set and 82% on 10 out-of-domain}(ood) test set. It is envisioned that this work will help in emulating human-human like topic transition in open-domain dialog systems.Comment: 5 pages, 4 figures, 3 table

Downward compatible revision of dialogue annotation

This paper discusses some aspects of revising the ISO standard for dialogue act annotation (ISO 24617-2). The revision is aimed at making annotations using the ISO scheme more accurate and at providing more powerful tools for building natural language based dialogue systems, without invalidating the annotated resources that have been built, with the current version of the standard. In support of the revision of the standard, an analysis is provided of the downward compatibility of a revised annotation scheme with the original scheme at the levels of abstract syntax, concrete syntax, and semantics of annotations

MILLA-Multimodal Interactive Language Learning Agent

Learning a new language involves the acquisition and integration of a range of skills. A human tu�tor aids learners by (i) providing tasks suitable to the learner’s needs, (ii) monitoring progress and adapting task content and delivery style, and (iii) providing a source of speaking practice and motivation

Polyaniline nanofibres as templates for the covalent immobilisation of biomolecules

The attachment of antibodies onto polyaniline nanofibres using covalent chemistry was investigated for the first time. Polyaniline nanofibres were functionalised post-polymerisation to attach either amide or carboxylic acid side-groups. These templates could then be further modified to attach antibodies, specifically in this instance mouse immunoglobulin G (IgG). The resultant conjugates were characterised using a variety of techniques including infrared, UV–vis and Raman spectroscopy. Conjugates were then used to detect secondary antibodies (anti-IgG). Results from enzyme-linked immunoassay studies indi- cate successful binding of the antibody to the polyaniline nanofibres. Carboxyl functionalised polyaniline nanofibres are shown in particular to decrease non-specific binding in the immunoassay. Direct electri- cal communication between polyaniline nanofibres covalently linked to peroxidase-labelled antibodies was observed during cyclic voltammetry, which demonstrates their potential for further development as nano-dimensional immunosensors

What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents

Conversational agents promise conversational interaction but fail to deliver. Efforts often emulate functional rules from human speech, without considering key characteristics that conversation must encapsulate. Given its potential in supporting long-term human-agent relationships, it is paramount that HCI focuses efforts on delivering this promise. We aim to understand what people value in conversation and how this should manifest in agents. Findings from a series of semi-structured interviews show people make a clear dichotomy between social and functional roles of conversation, emphasising the long-term dynamics of bond and trust along with the importance of context and relationship stage in the types of conversations they have. People fundamentally questioned the need for bond and common ground in agent communication, shifting to more utilitarian definitions of conversational qualities. Drawing on these findings we discuss key challenges for conversational agent design, most notably the need to redefine the design parameters for conversational agent interaction