The language of Evaluation: paralinguistic features as a phonological domain for appraisal

Bombelli, Griselda; Soler, Lidia Rosa; Waasaf, María Susana

doi:10.1590/s0102-44502013000200004

Cited by 3 publications

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“…In addition to enabling information exchange, auditory language provides important information about the speaker, their attitude and state of mind, as well as their relationship to the interlocutor (Liscombe et al, 2003;Bombelli et al, 2013). The impact of such paralinguistic voice features on the perception of a speaker's personality, emotional state, or the quality of the interaction remain a matter of debate.…”

Section: Auditory Perception Of Humanoidsmentioning

confidence: 99%

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

2020

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Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.Aim: To investigate which synthesized voice parameters predict the speaker's eeriness and voice likability; to determine if individual listener characteristics (e.g., personality, attitude toward robots, age) influence synthesized voice evaluations; and to explore which paralinguistic features subjectively distinguish humans from robots/artificial agents.Methods: 95 adults (62 females) listened to randomly presented audio-clips of three categories: synthesized (Watson, IBM), humanoid (robot Sophia, Hanson Robotics), and human voices (five clips/category). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. Contrary to the expectations of an uncanny valley, when the ratings of human-likeness for both the voice and the speaker characteristics were higher, they seemed less eerie to the participants. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.

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Section: Auditory Perception Of Humanoidsmentioning

confidence: 99%

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

2020

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Section: Auditory Perception Of Humanoidsmentioning

confidence: 99%

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Emotion in speech

Ariztimuño

Dreyfus

Moore

2022

LangCT

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This paper explores how emotion is conveyed in spoken language based on a sample of three stories for children read aloud by a trained storyteller. It draws on both Martin & White’s appraisal framework (2005) and a systematic account of vocal features. Interpreting and profiling emotion is a challenge both for researchers interested in spoken language and for English-as-an-additional-language teachers, when working to improve students’ spoken expression of emotion. Underpinning this challenge is the absence of a unified theoretical stance and a consequent lack of shared analytical tools for describing how speakers use semiotic resources to convey emotion in their speech. A systemic functional semiotic approach can make visible the co-patterning of wordings and vocalisations that express emotion.

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The language of Evaluation: paralinguistic features as a phonological domain for appraisal

Abstract: In this paper we explore the relationship between the language of evaluation and the use of paralinguistic features in reading aloud, relating Eggins & Slade's (1997) categories of appraisal with Brown's (1990)

Cited by 3 publications

References 1 publication

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

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Emotion in speech

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