Verbal communication is an expanding field in robotics showing a significant increase in both the industrial and research field. The application of verbal communication in robotics aims to reach a natural human-like interaction with robots. In this study, we investigated how salient terms related to verbal communication in robotics have evolved over the years, what are the topics that recur in the related literature, and what are their trends. The study is based on a computational linguistic analysis conducted on a database of 7,435 scientific publications over the last 2 decades. This comprehensive dataset was extracted from the Scopus database using specific key-words. Our results show how relevant terms of verbal communication evolved, which are the main coherent topics and how they have changed over the years. We highlighted positive and negative trends for the most coherent topics and the distribution over the years for the most significant ones. In particular, verbal communication resulted in being highly relevant for social robotics. Potentially, achieving natural verbal communication with a robot can have a great impact on the scientific, societal, and economic role of robotics in the future.

Verbal communication in robotics: a study on salient terms, research fields and trends in the last decades based on a computational linguistic analysis

Felice Dell'Orletta;
2021

Abstract

Verbal communication is an expanding field in robotics showing a significant increase in both the industrial and research field. The application of verbal communication in robotics aims to reach a natural human-like interaction with robots. In this study, we investigated how salient terms related to verbal communication in robotics have evolved over the years, what are the topics that recur in the related literature, and what are their trends. The study is based on a computational linguistic analysis conducted on a database of 7,435 scientific publications over the last 2 decades. This comprehensive dataset was extracted from the Scopus database using specific key-words. Our results show how relevant terms of verbal communication evolved, which are the main coherent topics and how they have changed over the years. We highlighted positive and negative trends for the most coherent topics and the distribution over the years for the most significant ones. In particular, verbal communication resulted in being highly relevant for social robotics. Potentially, achieving natural verbal communication with a robot can have a great impact on the scientific, societal, and economic role of robotics in the future.
Campo DC Valore Lingua
dc.authority.ancejournal FRONTIERS IN COMPUTER SCIENCE -
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC -
dc.authority.people Alessandro Marin Vargas it
dc.authority.people Lorenzo Cominelli it
dc.authority.people Felice Dell'Orletta it
dc.authority.people Enzo Pasquale Scilingo it
dc.collection.id.s b3f88f24-048a-4e43-8ab1-6697b90e068e *
dc.collection.name 01.01 Articolo in rivista *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/20 22:14:49 -
dc.date.available 2024/02/20 22:14:49 -
dc.date.issued 2021 -
dc.description.abstracteng Verbal communication is an expanding field in robotics showing a significant increase in both the industrial and research field. The application of verbal communication in robotics aims to reach a natural human-like interaction with robots. In this study, we investigated how salient terms related to verbal communication in robotics have evolved over the years, what are the topics that recur in the related literature, and what are their trends. The study is based on a computational linguistic analysis conducted on a database of 7,435 scientific publications over the last 2 decades. This comprehensive dataset was extracted from the Scopus database using specific key-words. Our results show how relevant terms of verbal communication evolved, which are the main coherent topics and how they have changed over the years. We highlighted positive and negative trends for the most coherent topics and the distribution over the years for the most significant ones. In particular, verbal communication resulted in being highly relevant for social robotics. Potentially, achieving natural verbal communication with a robot can have a great impact on the scientific, societal, and economic role of robotics in the future. -
dc.description.affiliations Department of Information Engineering (DII), University of Pisa, Pisa, Italy Department of Information Engineering (DII), University of Pisa, Pisa, Italy Istituto di Linguistica Computazionale, CNR, Pisa, Pisa Department of Information Engineering (DII), University of Pisa, Pisa, Italy -
dc.description.allpeople Alessandro Marin Vargas; Lorenzo Cominelli; Felice Dell'Orletta; Enzo Pasquale Scilingo -
dc.description.allpeopleoriginal Alessandro Marin Vargas, Lorenzo Cominelli, Felice Dell'Orletta, Enzo Pasquale Scilingo -
dc.description.fulltext none en
dc.description.note qaqw -
dc.description.numberofauthors 1 -
dc.identifier.doi 10.3389/fcomp.2020.591164 -
dc.identifier.uri https://hdl.handle.net/20.500.14243/400917 -
dc.language.iso eng -
dc.subject.keywords social robotics -
dc.subject.keywords affective computing -
dc.subject.keywords speech synthesis -
dc.subject.keywords speech generation -
dc.subject.keywords computational linguistic analysis -
dc.subject.keywords data mining -
dc.subject.keywords topic modeling -
dc.subject.keywords verbal communication -
dc.subject.singlekeyword social robotics *
dc.subject.singlekeyword affective computing *
dc.subject.singlekeyword speech synthesis *
dc.subject.singlekeyword speech generation *
dc.subject.singlekeyword computational linguistic analysis *
dc.subject.singlekeyword data mining *
dc.subject.singlekeyword topic modeling *
dc.subject.singlekeyword verbal communication *
dc.title Verbal communication in robotics: a study on salient terms, research fields and trends in the last decades based on a computational linguistic analysis en
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dc.type.referee Sì, ma tipo non specificato -
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