Finding reliable resources and Chatting with Mira while considering emotions when the scenario is unscripted

• Author / Creator

  Gharaat, Mohamad Ali

• The primary wellspring of information, the Internet, abounds with misinfor-
  mation, particularly in the domains of mental health and psychology. This also
  affects the reliability and truth of responses of chatbots counting on unverified
  data.
  To address this concern, the MIRA project started to create a reliable
  source of information and develop a chatbot that can deliver these verified
  resources of information. By respecting privacy, anonymity of user data, MIRA
  seeks to support individuals looking for a safe environment to find information
  and assistance in their mental health journey.
  The MIRA Project consists of the MIRA resource library and the MIRA
  chatbot. In this thesis we develop the MIRA resource library in which our
  domain experts define, edit, and evaluate resources. This also includes a re-
  source search functionality that allows the MIRA chatbot to search efficiently
  among the verified resources.
  The MIRA chatbot employs scripted questions to detect user intents and
  entities. In this thesis we add Chatty MIRA for producing empathetic replies
  for scenarios in which the user is looking for just a conversation with the MIRA
  chatbot. Chatty MIRA facilitates a rule-based text generator and an emotion
  detection component, proficient in identifying emotions and producing em-
  pathetic replies. As users engage in casual conversations with Chatty MIRA,
  Chatty MIRA can simultaneously attempt to search for related resources based
  on detected intents and entities. This allows for a more engaging experience
  for the end-user, where MIRA can provide empathetic responses while also
  offering relevant resources to support the users with relevant resources it can
  find.
  We conduct a human evaluation to assess the superiority of Chatty MIRA
  over its rule-based and Large Language Model (LLM) competitors. As well as
  determine the gap between Chatty MIRA and advanced LLMs (i.e. GPT-3.5).

• Subjects / Keywords

  • Chatbot
  • NLP
  • Sentiment Analysis
  • Emotion Detection
  • Mental Health

• Graduation date

  Spring 2024

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-hw18-jq52

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.