Artificial Personality and Disfluency

The focus of this paper is artificial voices with different person-alities. Previous studies have shown links between an individ-ual’s use of disfluencies in their speech and their perceived per-sonality. Here, filled pauses (uh and um) and discourse markers (like, you know, I mean) have been included in synthetic speech as a way of creating an artificial voice with different personali-ties. We discuss the automatic insertion of filled pauses and dis-course markers (i.e., fillers) into otherwise fluent texts. The au-tomatic system is compared to a ground truth of human “acted” filler insertion. Perceived personality (as defined by the big five personality dimensions) of the synthetic speech is assessed by means of a standardised questionnaire. Synthesis without fillers is compared to synthesis with either spontaneous or synthetic fillers. Our findings explore how the inclusion of disfluencies influences the way in which subjects rate the perceived person-ality of an artificial voice. Index Terms: artificial personality, TTS, disfluency 1

A Framework of Personality Cues for Conversational Agents

Conversational agents (CAs)—software systems emulating conversations with humans through natural language—reshape our communication environment. As CAs have been widely used for applications requiring human-like interactions, a key goal in information systems (IS) research and practice is to be able to create CAs that exhibit a particular personality. However, existing research on CA personality is scattered across different fields and researchers and practitioners face difficulty in understanding the current state of the art on the design of CA personality. To address this gap, we systematically analyze existing studies and develop a framework on how to imbue CAs with personality cues and how to organize the underlying range of expressive variation regarding the Big Five personality traits. Our framework contributes to IS research by providing an overview of CA personality cues in verbal and non-verbal language and supports practitioners in designing CAs with a particular personality

Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectives

Disfluencies (i.e. interruptions in the regular flow of speech), are ubiquitous to spoken discourse. Fillers ("uh", "um") are disfluencies that occur the most frequently compared to other kinds of disfluencies. Yet, to the best of our knowledge, there isn't a resource that brings together the research perspectives influencing Spoken Language Understanding (SLU) on these speech events. This aim of this article is to synthesise a breadth of perspectives in a holistic way; i.e. from considering underlying (psycho)linguistic theory, to their annotation and consideration in Automatic Speech Recognition (ASR) and SLU systems, to lastly, their study from a generation standpoint. This article aims to present the perspectives in an approachable way to the SLU and Conversational AI community, and discuss moving forward, what we believe are the trends and challenges in each area.Comment: To appear in TAL Journa

Speakers Raise their Hands and Head during Self-Repairs in Dyadic Conversations

People often encounter difficulties in building shared understanding during everyday conversation. The most common symptom of these difficulties are self-repairs, when a speaker restarts, edits or amends their utterances mid-turn. Previous work has focused on the verbal signals of self-repair, i.e. speech disfluences (filled pauses, truncated words and phrases, word substitutions or reformulations), and computational tools now exist that can automatically detect these verbal phenomena. However, face-to-face conversation also exploits rich non-verbal resources and previous research suggests that self-repairs are associated with distinct hand movement patterns. This paper extends those results by exploring head and hand movements of both speakers and listeners using two motion parameters: height (vertical position) and 3D velocity. The results show that speech sequences containing self-repairs are distinguishable from fluent ones: speakers raise their hands and head more (and move more rapidly) during self-repairs. We obtain these results by analysing data from a corpus of 13 unscripted dialogues, and we discuss how these findings could support the creation of improved cognitive artificial systems for natural human-machine and human-robot interaction

Destabilized Artistry in the Rhetorical Presidency

The presidency was once a carefully scripted and carefully controlled site of speech production. Today’s media environment has not lessened efforts at control, but it has rendered these efforts increasingly difficult. Previously disruptive and disfluent ways of speaking now serve a useful role in presidential address, allowing mass-mediated audiences to apprehend the presidency in ways that appear to be more intimate and more authentic than careful scripting allows. In response to this new and fast-evolving rhetorical landscape, this essay develops an analytically, historically, and conceptually wide-ranging argument, inviting rhetorical scholars to supplement their abiding interest in traditional forms of presidential eloquence with a commitment to the study of presidential disfluency. Awkward pauses, verbal hiccups, botched colloquialisms, confessionals, and overly personalized speech all transgress the norms and expectations of presidential eloquence, allowing scholars to reflect on the longstanding, rhetorical discrepancy between presidential speech as it appears in the official historical record and presidential speech as mass-mediated audiences actually hear it

Processing Fluency in Education: How Metacognitive Feelings Shape Learning, Belief Formation, and Affect

Processing fluency—the experienced ease with which a mental operation is performed has attracted little attention in educational psychology, despite its relevance. The present article reviews and integrates empirical evidence on processing fluency that is relevant to school education. Fluency is important, for instance, in learning, self-assessment of knowledge, testing, grading, teacher–student communication, social interaction in the multicultural classroom, and emergence of interest. After a brief overview of basic fluency research we review effects of processing fluency in three broad areas: metacognition in learning, belief formation, and affect. Within each area, we provide evidence-based implications for education. Along the way, we offer fluency-based insights into phenomena that were long known but not yet sufficiently explained (e.g., the effect of handwriting on grading). Bringing fluency (back) to education may contribute to research and school practice alike