UTAR Institutional Repository

Mental healthcare chatbot

Oon, Xin Yi (2021) Mental healthcare chatbot. Final Year Project, UTAR.

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    Abstract

    More and more mental health issues such as depression are getting known and recognized by our society today. However, not all of them can receive appropriate treatment. There are many of us still facing the problem of getting the appropriate mental health services every day. We cannot deny the fact that not everyone can get mental healthcare services as they might face some difficulties such as financial problems. Therefore, we may look for new solutions to fix this mental health issue. This demand for solving this issue has led to the proposal of technology as a solution. Chatbot, also known as a conversational agent which can participate in the conversation might be considered one of the solutions too. By mimicking the conversation between human counselor and patient, it can provide counselor service to the patient at some point. However, to further improve the quality of the counselor service, the improvement of the chatbot has to be carried out. By using deep learning, this proposed chatbot can recognize the meaning of the conversation and give a relevant response. Moreover, by using speech reorganization and speech synthesis, the chatbot can serve people in more ways. For example, those who are blind can use this chatbot by speaking to the chatbot and receive the output by listening to the sound. Moreover, this chatbot also able to serve those has a listening problem since they can just read the sentences that output by the chatbot.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    T Technology > T Technology (General)
    Divisions: Faculty of Information and Communication Technology > Bachelor of Computer Science (Hons)
    Depositing User: ML Main Library
    Date Deposited: 09 Mar 2022 20:58
    Last Modified: 09 Mar 2022 20:58
    URI: http://eprints.utar.edu.my/id/eprint/4269

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