Cargando…
Counseling (ro)bot as a use case for 5G/6G
This paper presents a counseling (ro)bot called Visual Counseling Agent (VICA) which focuses on remote mental healthcare. It is an agent system leveraging artificial intelligence (AI) to aid mentally distressed persons through speech conversation. The system terminals are connected to servers by the...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8965220/ https://www.ncbi.nlm.nih.gov/pubmed/35369530 http://dx.doi.org/10.1007/s40747-022-00664-2 |
_version_ | 1784678382564278272 |
---|---|
author | Taniguchi, Yoshio Ikegami, Yukino Fujikawa, Hiroshi Pathare, Yogesh Kutics, Andrea Massimo, Banzi Anisetti, Marco Damiani, Ernesto Sakurai, Yoshitaka Tsuruta, Setsuo |
author_facet | Taniguchi, Yoshio Ikegami, Yukino Fujikawa, Hiroshi Pathare, Yogesh Kutics, Andrea Massimo, Banzi Anisetti, Marco Damiani, Ernesto Sakurai, Yoshitaka Tsuruta, Setsuo |
author_sort | Taniguchi, Yoshio |
collection | PubMed |
description | This paper presents a counseling (ro)bot called Visual Counseling Agent (VICA) which focuses on remote mental healthcare. It is an agent system leveraging artificial intelligence (AI) to aid mentally distressed persons through speech conversation. The system terminals are connected to servers by the Internet exploiting Cloud-nativeness, so that anyone who has any type of terminal can use it from anywhere. Despite a promising voice communication interface, VICA shows limitations in conversation continuity on conventional 4G networks. Concretely, the use of the current 4G networks produces word dropping, delayed response, and the occasional connection failure. The objective of this paper is to mitigate these issues by leveraging a 5G/6G slice inclusive of mobile/multiple edge computing (MEC). First, we propose and partly implement the enhanced and advanced version of VICA. Servers of enhanced versions collaborate to increase speech recognition reliability. Although it significantly increases generated data volume, the advanced version enables a recognition of the facial expressions to greatly enhance counseling quality. Then, we propose a quality assurance mechanism using multiple levels of catalog, as well as 5G/6G slice inclusive of MEC, and conduct experiments to uncover issues related to the 4G. Results indicate that the number of speech recognition errors in Internet Cloud is more than twofold compared to edge computing, implying that quality assurance using 5G/6G in conjunction with VICA Counseling (ro)bot has higher efficiency. |
format | Online Article Text |
id | pubmed-8965220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-89652202022-03-30 Counseling (ro)bot as a use case for 5G/6G Taniguchi, Yoshio Ikegami, Yukino Fujikawa, Hiroshi Pathare, Yogesh Kutics, Andrea Massimo, Banzi Anisetti, Marco Damiani, Ernesto Sakurai, Yoshitaka Tsuruta, Setsuo Complex Intell Systems Original Article This paper presents a counseling (ro)bot called Visual Counseling Agent (VICA) which focuses on remote mental healthcare. It is an agent system leveraging artificial intelligence (AI) to aid mentally distressed persons through speech conversation. The system terminals are connected to servers by the Internet exploiting Cloud-nativeness, so that anyone who has any type of terminal can use it from anywhere. Despite a promising voice communication interface, VICA shows limitations in conversation continuity on conventional 4G networks. Concretely, the use of the current 4G networks produces word dropping, delayed response, and the occasional connection failure. The objective of this paper is to mitigate these issues by leveraging a 5G/6G slice inclusive of mobile/multiple edge computing (MEC). First, we propose and partly implement the enhanced and advanced version of VICA. Servers of enhanced versions collaborate to increase speech recognition reliability. Although it significantly increases generated data volume, the advanced version enables a recognition of the facial expressions to greatly enhance counseling quality. Then, we propose a quality assurance mechanism using multiple levels of catalog, as well as 5G/6G slice inclusive of MEC, and conduct experiments to uncover issues related to the 4G. Results indicate that the number of speech recognition errors in Internet Cloud is more than twofold compared to edge computing, implying that quality assurance using 5G/6G in conjunction with VICA Counseling (ro)bot has higher efficiency. Springer International Publishing 2022-03-30 2022 /pmc/articles/PMC8965220/ /pubmed/35369530 http://dx.doi.org/10.1007/s40747-022-00664-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Taniguchi, Yoshio Ikegami, Yukino Fujikawa, Hiroshi Pathare, Yogesh Kutics, Andrea Massimo, Banzi Anisetti, Marco Damiani, Ernesto Sakurai, Yoshitaka Tsuruta, Setsuo Counseling (ro)bot as a use case for 5G/6G |
title | Counseling (ro)bot as a use case for 5G/6G |
title_full | Counseling (ro)bot as a use case for 5G/6G |
title_fullStr | Counseling (ro)bot as a use case for 5G/6G |
title_full_unstemmed | Counseling (ro)bot as a use case for 5G/6G |
title_short | Counseling (ro)bot as a use case for 5G/6G |
title_sort | counseling (ro)bot as a use case for 5g/6g |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8965220/ https://www.ncbi.nlm.nih.gov/pubmed/35369530 http://dx.doi.org/10.1007/s40747-022-00664-2 |
work_keys_str_mv | AT taniguchiyoshio counselingrobotasausecasefor5g6g AT ikegamiyukino counselingrobotasausecasefor5g6g AT fujikawahiroshi counselingrobotasausecasefor5g6g AT pathareyogesh counselingrobotasausecasefor5g6g AT kuticsandrea counselingrobotasausecasefor5g6g AT massimobanzi counselingrobotasausecasefor5g6g AT anisettimarco counselingrobotasausecasefor5g6g AT damianiernesto counselingrobotasausecasefor5g6g AT sakuraiyoshitaka counselingrobotasausecasefor5g6g AT tsurutasetsuo counselingrobotasausecasefor5g6g |