Enhancing EmoBot: An In-Depth Analysis of User Satisfaction and Faults in an Emotion-Aware Chatbot

TL;DR

This paper critically analyzes EmoBot, an emotion-aware chatbot, assessing user satisfaction and faults, and proposes solutions to improve its usability, accuracy, and fault tolerance based on comprehensive evaluations.

Contribution

It provides an in-depth evaluation of EmoBot's performance and introduces targeted solutions to enhance its emotional generation capabilities and fault tolerance.

Findings

Identified key shortcomings in EmoBot's performance

Survey results highlight user dissatisfaction areas

Proposed solutions improve fault tolerance and usability

Abstract

The research community has traditionally shown a keen interest in emotion modeling, with a notable emphasis on the detection aspect. In contrast, the exploration of emotion generation has received less attention.This study delves into an existing state-of-the-art emotional chatbot, EmoBot, designed for generating emotions in general-purpose conversations. This research involves a comprehensive examination, including a survey to evaluate EmoBot's proficiency in key dimensions like usability, accuracy, and overall user satisfaction, with a specific focus on fault tolerance. By closely examining the chatbot's operations, we identified some noteworthy shortcomings in the existing model. We propose some solutions designed to address and overcome the identified issues.