Evidence map›Paper›PMID 35161737›Full record

ArticleSensors (Basel, Switzerland)2022

A Preliminary Study on Realizing Human-Robot Mental Comforting Dialogue via Sharing Experience Emotionally.

Changzeng Fu, Qi Deng, Jingcheng Shen, Hamed Mahzoon, Hiroshi Ishiguro

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Mobile robots for isolation-room hospital settings: A scenario-based preliminary study.Computational and structural biotechnology journal · 2024
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Changzeng FuGraduate School of Engineering Science, Osaka University, Toyonaka 560-8531, Japan.
Qi DengGraduate School of Intercultural Studies, Kobe University, Kobe 657-8501, Japan.
Jingcheng ShenGraduate School of Information Science, Osaka University, Suita 565-0871, Japan.
Hamed MahzoonGraduate School of Engineering Science, Osaka University, Toyonaka 560-8531, Japan.ORCID 0000-0001-6066-259X
Hiroshi IshiguroGraduate School of Engineering Science, Osaka University, Toyonaka 560-8531, Japan.

Funding

JST, Moonshot R&D , Japan JPMJMS2011
6 · The paper itself

Abstract

Mental health issues are receiving more and more attention in society. In this paper, we introduce a preliminary study on human-robot mental comforting conversation, to make an android robot (ERICA) present an understanding of the user's situation by sharing similar emotional experiences to enhance the perception of empathy. Specifically, we create the emotional speech for ERICA by using CycleGAN-based emotional voice conversion model, in which the pitch and spectrogram of the speech are converted according to the user's mental state. Then, we design dialogue scenarios for the user to talk about his/her predicament with ERICA. In the dialogue, ERICA shares other people's similar predicaments and adopts a low-spirit voice to express empathy to the interlocutor's situation. At the end of the dialogue, ERICA tries to encourage with a positive voice. Subsequently, questionnaire-based evaluation experiments were conducted with the recorded conversation. In the questionnaire, we use the Big Five scale to evaluate ERICA's personality. In addition, the perception of emotion, empathy, and encouragement in the dialogue are evaluated. The results show that the proposed emotional expression strategy helps the android robot better present low-spirit emotion, empathy, the personality of extroversion, while making the user better feel the encouragement.

Indexed as

RoboticsCommunicationEmotionsEmpathyFemaleHumansMalePersonalityemotional interactionexperience sharinghuman–robot conversation

Identifiers

PMID35161737
PMCPMC8838416

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.