Abstract
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.
Highlights
Sentiment analysis is a technology that perceives the pattern of human emotion and is commonly used as a supplement in treating mental issues
This paper proposed a new smart mirror, LUX, that provides sentiment analysis of
This paper proposed a new smart mirror, LUX, that provides sentiment analysis of human speech, supporting a more comfortable lifestyle to complement the exhausting rehuman speech, supporting a more comfortable lifestyle to complement the exhausting ality
Summary
Sentiment analysis is a technology that perceives the pattern of human emotion and is commonly used as a supplement in treating mental issues. The growing market of smart mirrors and their extensibility from familiar hardware inspired this paper to suggest applying sentiment analysis to this particular AI device. The analysis results showed that this algorithm enhanced upright posture at a considerable rate These studies demonstrate the rationale of implementing sentiment analysis in smart mirrors. Recent sentiment analysis studies have investigated voice intonation, facial emotion detection, and text-based algorithms that use deep learning algorithms to solve NLP tasks. LUX returns different responses to each sentiment with the purpose of making the user feel better These responses include reciting wise sayings, empathizing, and playing MP3 music as music therapy. Using a deep learning model to build a smart mirror with user sentiment analysis, and, Providing responses that encourage specific emotions in users.
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