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LUX: Smart Mirror with Sentiment Analysis for Mental Comfort

As COVID-19 solidifies its presence in everyday life, the interest in mental health is growing, resulting in the necessity of sentiment analysis. A smart mirror is suitable for encouraging mental comfort due to its approachability and scalability as an in-home AI device. From the aspect of natural l...

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Detalles Bibliográficos
Autores principales: Yu, Hyona, Bae, Jihyun, Choi, Jiyeon, Kim, Hyungseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125726/
https://www.ncbi.nlm.nih.gov/pubmed/33946700
http://dx.doi.org/10.3390/s21093092
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author Yu, Hyona
Bae, Jihyun
Choi, Jiyeon
Kim, Hyungseok
author_facet Yu, Hyona
Bae, Jihyun
Choi, Jiyeon
Kim, Hyungseok
author_sort Yu, Hyona
collection PubMed
description As COVID-19 solidifies its presence in everyday life, the interest in mental health is growing, resulting in the necessity of sentiment analysis. A smart mirror is suitable for encouraging mental comfort due to its approachability and scalability as an in-home AI device. From the aspect of natural language processing (NLP), sentiment analysis for Korean lacks an emotion dataset regarding everyday conversation. Its significant differences from English in terms of language structure make implementation challenging. The proposed smart mirror LUX provides Korean text sentiment analysis with the deep learning model, which examines GRU, LSTM, CNN, Bi-LSTM, and Bi-GRU networks. There are four emotional labels: anger, sadness, neutral, and happiness. For each emotion, there are three possible interactive responses: reciting wise sayings, playing music, and sympathizing. The implemented smart mirror also includes more-typical functions, such as a wake-up prompt, a weather reporting function, a calendar, a news reporting function, and a clock.
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spelling pubmed-81257262021-05-17 LUX: Smart Mirror with Sentiment Analysis for Mental Comfort Yu, Hyona Bae, Jihyun Choi, Jiyeon Kim, Hyungseok Sensors (Basel) Article As COVID-19 solidifies its presence in everyday life, the interest in mental health is growing, resulting in the necessity of sentiment analysis. A smart mirror is suitable for encouraging mental comfort due to its approachability and scalability as an in-home AI device. From the aspect of natural language processing (NLP), sentiment analysis for Korean lacks an emotion dataset regarding everyday conversation. Its significant differences from English in terms of language structure make implementation challenging. The proposed smart mirror LUX provides Korean text sentiment analysis with the deep learning model, which examines GRU, LSTM, CNN, Bi-LSTM, and Bi-GRU networks. There are four emotional labels: anger, sadness, neutral, and happiness. For each emotion, there are three possible interactive responses: reciting wise sayings, playing music, and sympathizing. The implemented smart mirror also includes more-typical functions, such as a wake-up prompt, a weather reporting function, a calendar, a news reporting function, and a clock. MDPI 2021-04-29 /pmc/articles/PMC8125726/ /pubmed/33946700 http://dx.doi.org/10.3390/s21093092 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Hyona
Bae, Jihyun
Choi, Jiyeon
Kim, Hyungseok
LUX: Smart Mirror with Sentiment Analysis for Mental Comfort
title LUX: Smart Mirror with Sentiment Analysis for Mental Comfort
title_full LUX: Smart Mirror with Sentiment Analysis for Mental Comfort
title_fullStr LUX: Smart Mirror with Sentiment Analysis for Mental Comfort
title_full_unstemmed LUX: Smart Mirror with Sentiment Analysis for Mental Comfort
title_short LUX: Smart Mirror with Sentiment Analysis for Mental Comfort
title_sort lux: smart mirror with sentiment analysis for mental comfort
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125726/
https://www.ncbi.nlm.nih.gov/pubmed/33946700
http://dx.doi.org/10.3390/s21093092
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