SLIIT Conference and Symposium Proceedings

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All SLIIT faculties annually conduct international conferences and symposiums. Publications from these events are included in this collection.

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Subject: search.filters.subject.Voice Analysis

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    PublicationOpen Access
    Smart Chat: A Mobile Chat Application Based on Machine Learning
    (SLIIT City UNI, 2025-07-08) Yathuraj, G; Abeysinghe, A
    In an increasingly digital world, communication is primarily conducted through messaging apps, but these platforms cannot often convey emotional nuance. This limitation can lead to misunderstandings, emotional disconnects, and deteriorating relationships. SmartChat addresses this gap by integrating machine learning-based emotion recognition into a mobile chat app, allowing users to send and receive voice messages enriched with emotional context. Built using React Native and compatible with both Android and iOS, SmartChat analyzes voice cues such as tone, pitch, and cadence to detect and display emotions to the user. This innovation improves the clarity and empathy of conversations, making digital communications more humancentered. Beyond general messaging, SmartChat has the potential to be used in critical contexts such as education, mental health support, and emotional literacy. By making emotionally aware communication accessible across languages and cultures, SmartChat contributes to fostering healthy interpersonal relationships and supports the broader goal of social sustainability through technology.
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    PublicationEmbargo
    AI Based Depression and Suicide Prevention System
    (2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Kulasinghe, S.A.S.A.; Jayasinghe, A.; Rathnayaka, R.M.A.; Karunarathne, P.B.M.M.D.; Silva, P.D.S.; Anuradha Jayakodi, J.A.D.C.
    Suicide is a major issue in the world. The number one reason for suicide is untreated depression. That is why it was decided to focus on depression symptoms more and identify them in order to prevent suicidal attempts. To cure depression, the best way is to talk about their feelings with someone they trusted and release their pain inside of them. Because of that this system has a Chat-bot for the user to interact with. Chat-bot will gather information about the users feelings through text and voice analysis. Also by analyzing their Facebook statuses and recent web history, the application gather more information about their mental state so that the system take more accurate conclusions. After analyzing all the information from each component the back brain will decide on how the chat-bot should act on the user. At the end, the product was able to give more than 75% accurate results for each component.