Sound Synthesis for Communicating Nonverbal Expressive Cues

Non-verbal sounds (NVS) constitute an appealing communicative channel for transmitting a message during a dialog. They provide two main benefits, such as they are not linked to any particular language, and they can express a message in a short time. NVS have been successfully used in robotics, cell...

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Main Authors: Javier Fernandez De Gorostiza luengo, Fernando Alonso Martin, Alvaro Castro-Gonzalez, Miguel Angel Salichs
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7839199/
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spelling doaj-71a4ae1a090444e49303ce63e84874c92021-03-29T19:59:37ZengIEEEIEEE Access2169-35362017-01-0151941195710.1109/ACCESS.2017.26587267839199Sound Synthesis for Communicating Nonverbal Expressive CuesJavier Fernandez De Gorostiza luengo0Fernando Alonso Martin1https://orcid.org/0000-0003-3013-968XAlvaro Castro-Gonzalez2Miguel Angel Salichs3Universidad Carlos III de Madrid, Madrid, SpainUniversidad Carlos III de Madrid, Madrid, SpainUniversidad Carlos III de Madrid, Madrid, SpainUniversidad Carlos III de Madrid, Madrid, SpainNon-verbal sounds (NVS) constitute an appealing communicative channel for transmitting a message during a dialog. They provide two main benefits, such as they are not linked to any particular language, and they can express a message in a short time. NVS have been successfully used in robotics, cell phones, and science fiction films. However, there is a lack of deep studies on how to model NVS. For instance, most of the systems for NVS expression are ad hoc solutions that focus on the communication of the most prominent emotion. Only a small number of papers have proposed a more general model or dealt directly with the expression of pure communicative acts, such as affirmation, denial, or greeting. In this paper we propose a system, referred to as the sonic expression system (SES), that is able to generate NVS on the fly by adapting the sound to the context of the interaction. The system is designed to be used by social robots while conducting human-robot interactions. It is based on a model that includes several acoustic features from the amplitude, frequency, and time spaces. In order to evaluate the capabilities of the system, nine categories of communicative acts were created. By means of an online questionnaire, 51 participants classified the utterances according to their meaning, such as agreement, hesitation, denial, hush, question, summon, encouragement, greetings, and laughing. The results showed how very different NVS generated by our SES can be used for communicating.https://ieeexplore.ieee.org/document/7839199/Sound synthesisHuman–Robot InteractionElectrosonic modeSocial RobotsNon-Verbal SoundsSonic mode
collection DOAJ
language English
format Article
sources DOAJ
author Javier Fernandez De Gorostiza luengo
Fernando Alonso Martin
Alvaro Castro-Gonzalez
Miguel Angel Salichs
spellingShingle Javier Fernandez De Gorostiza luengo
Fernando Alonso Martin
Alvaro Castro-Gonzalez
Miguel Angel Salichs
Sound Synthesis for Communicating Nonverbal Expressive Cues
IEEE Access
Sound synthesis
Human–Robot Interaction
Electrosonic mode
Social Robots
Non-Verbal Sounds
Sonic mode
author_facet Javier Fernandez De Gorostiza luengo
Fernando Alonso Martin
Alvaro Castro-Gonzalez
Miguel Angel Salichs
author_sort Javier Fernandez De Gorostiza luengo
title Sound Synthesis for Communicating Nonverbal Expressive Cues
title_short Sound Synthesis for Communicating Nonverbal Expressive Cues
title_full Sound Synthesis for Communicating Nonverbal Expressive Cues
title_fullStr Sound Synthesis for Communicating Nonverbal Expressive Cues
title_full_unstemmed Sound Synthesis for Communicating Nonverbal Expressive Cues
title_sort sound synthesis for communicating nonverbal expressive cues
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2017-01-01
description Non-verbal sounds (NVS) constitute an appealing communicative channel for transmitting a message during a dialog. They provide two main benefits, such as they are not linked to any particular language, and they can express a message in a short time. NVS have been successfully used in robotics, cell phones, and science fiction films. However, there is a lack of deep studies on how to model NVS. For instance, most of the systems for NVS expression are ad hoc solutions that focus on the communication of the most prominent emotion. Only a small number of papers have proposed a more general model or dealt directly with the expression of pure communicative acts, such as affirmation, denial, or greeting. In this paper we propose a system, referred to as the sonic expression system (SES), that is able to generate NVS on the fly by adapting the sound to the context of the interaction. The system is designed to be used by social robots while conducting human-robot interactions. It is based on a model that includes several acoustic features from the amplitude, frequency, and time spaces. In order to evaluate the capabilities of the system, nine categories of communicative acts were created. By means of an online questionnaire, 51 participants classified the utterances according to their meaning, such as agreement, hesitation, denial, hush, question, summon, encouragement, greetings, and laughing. The results showed how very different NVS generated by our SES can be used for communicating.
topic Sound synthesis
Human–Robot Interaction
Electrosonic mode
Social Robots
Non-Verbal Sounds
Sonic mode
url https://ieeexplore.ieee.org/document/7839199/
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AT alvarocastrogonzalez soundsynthesisforcommunicatingnonverbalexpressivecues
AT miguelangelsalichs soundsynthesisforcommunicatingnonverbalexpressivecues
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