The project is based on a chat bot which will communicate with people in order to identify whether the particular person has depression or not. It will talk to people as their friends and can identify their mental state. Front end will be an android application that will work on user?s mobile ph
Depression Detector Chatbot
The project is based on a chat bot which will communicate with people in order to identify whether the particular person has depression or not. It will talk to people as their friends and can identify their mental state. Front end will be an android application that will work on user’s mobile phone and the backend will be on python that will determine the depression or anxiety through natural language processing.
To develop a friendly application (chat bot) which can talk with person as friend in order to determine his/her mental state.
In this project, the Natural Language Processing (NLP) technique will be used to make inferences about people’s mental state. These inferences can then be used to create online pathways to direct people to health information and assistance and also to generate personalized interventions. We plan to create a large-scale dataset of users with self-reported-depression messages. Several correlational analyses will be performed to understand the psycho-social-behaviors. Moreover, we will apply machine learning (ML) methods to build behavior prediction tools using the back Depression Inventory (BDI). We believe that the BD will be a valuable resource to be used by linguists, sociologists, computer scientists, psychologists.
One notable benefit of chatbots is that engineers can program them to implement techniques widelyaccepted as advantageous in the psychological field. For example, Woebot is a chatbot that usescognitive behavioral therapy strategies to help users manage symptoms of anxiety and depression.
1. The outcome will be a mobile app which will communicate with a user and predict thedepression of a user.
2. A friendly chatbot which act like a friend.
3. Mobile application will be based on Android.
4. Backend will be on Python Django framework.
5. The server will be hosted on AWS as it will require tremendous amount of processing.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| AWS Server C5 d.large Instance per hour | Equipment | 0 | 0 | 0 |
| NLP and RNN courses | Miscellaneous | 2 | 5000 | 10000 |
| Total in (Rs) | 10000 |
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