Smart companion agent for mental well-being through Deep Learning and NLP
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
| Main Authors: | , , , , |
|---|---|
| 其他作者: | |
| 格式: | Thesis |
| 语言: | English |
| 出版: |
Brac University
2021
|
| 主题: | |
| 在线阅读: | http://hdl.handle.net/10361/14973 |
| id |
10361-14973 |
|---|---|
| record_format |
dspace |
| spelling |
10361-149732022-01-26T10:04:52Z Smart companion agent for mental well-being through Deep Learning and NLP Khan, Rafiur Sohel, Abdullah Al Shreyashee, Farhana Azad Hossain, Shamima Fiaz, Mahin Alam, Md. Golam Rabiul Rasel, Mr. Annajiat Alim Department of Computer Science and Engineering, Brac University BioBERT Transformer Mental health Machine learning techniques Signals Deep Learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 60-62). Mental disorders are an unfortunate reality among the general population nowadays. Conditions like anxiety; depression may seem trivial on the surface but have serious consequences on an individual’s life. These disorders have shown to be detrimental to health and hamper a person’s general well being. In severe cases, if mental disorders go unnoticed and untreated they can cause permanent damage to one’s personality, drive him/her to social isolation and in worst cases compel the person to commit suicide as a means to end their suffering. Therefore, a need for proper detection and awareness of such diseases in a person emerges. Mental disorders may not show physical symptoms in a person but it is possible to find patterns in people with a potential mental disorder and detect them with the help of modern Machine learning techniques. In addition to this, such methods are completely automated and non-invasive; as a result these systems can also help continuously monitor a person’s mental state. We propose a system that can take various physiological signal readings from the human body as a way to predict distress. Upon detecting a user’s distress, the system tries to converse with the user trained by a knowledge base of conversations of people suffering from mental disorders and can interact with the user in a conversation-like interface as a companion. For this we used a system consisting of BioBERT models(separately for questions and answers) and a couple of FCNN layers. Rafiur Khan Abdullah Al Sohel Farhana Azad Shreyashee Shamima Hossain Mahin Fiaz B. Computer Science 2021-09-05T06:41:39Z 2021-09-05T06:41:39Z 2021 2021-01 Thesis ID 16101087 ID 19341008 ID 16101096 ID 17101429 ID 16101269 http://hdl.handle.net/10361/14973 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 62 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
BioBERT Transformer Mental health Machine learning techniques Signals Deep Learning |
| spellingShingle |
BioBERT Transformer Mental health Machine learning techniques Signals Deep Learning Khan, Rafiur Sohel, Abdullah Al Shreyashee, Farhana Azad Hossain, Shamima Fiaz, Mahin Smart companion agent for mental well-being through Deep Learning and NLP |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Alam, Md. Golam Rabiul |
| author_facet |
Alam, Md. Golam Rabiul Khan, Rafiur Sohel, Abdullah Al Shreyashee, Farhana Azad Hossain, Shamima Fiaz, Mahin |
| format |
Thesis |
| author |
Khan, Rafiur Sohel, Abdullah Al Shreyashee, Farhana Azad Hossain, Shamima Fiaz, Mahin |
| author_sort |
Khan, Rafiur |
| title |
Smart companion agent for mental well-being through Deep Learning and NLP |
| title_short |
Smart companion agent for mental well-being through Deep Learning and NLP |
| title_full |
Smart companion agent for mental well-being through Deep Learning and NLP |
| title_fullStr |
Smart companion agent for mental well-being through Deep Learning and NLP |
| title_full_unstemmed |
Smart companion agent for mental well-being through Deep Learning and NLP |
| title_sort |
smart companion agent for mental well-being through deep learning and nlp |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14973 |
| work_keys_str_mv |
AT khanrafiur smartcompanionagentformentalwellbeingthroughdeeplearningandnlp AT sohelabdullahal smartcompanionagentformentalwellbeingthroughdeeplearningandnlp AT shreyasheefarhanaazad smartcompanionagentformentalwellbeingthroughdeeplearningandnlp AT hossainshamima smartcompanionagentformentalwellbeingthroughdeeplearningandnlp AT fiazmahin smartcompanionagentformentalwellbeingthroughdeeplearningandnlp |
| _version_ |
1814306991957344256 |