The problem Sentyector solves

During the time of pandemic people have faced with new realities of working from home, temporary unemployment, and lack physical contact with other family members, friends, and colleagues, a lot more change in the mental health.

In today's usage, there exists a generation gap between younger people and their parents or grandparents. The differences lie in not understanding each other because of their differences in experiences, opinions, habits, and behavior.

A special concern for a person suffering from issues in emotional, psychological, and social well-being. How the person is thinking, feeling and what are the problems that are being faced by an individual.

1.)Implementation (Android app): The users give the input in the audio format, chunking of input is done, then the input is passed through the speech-to-text module where every chunk/sentence is converted to text which predicts the sentiments, and the dynamic graph is created for each and every line. So that a person can easily come to know in what way he/she is talking.
With the help of the selector, one can easily analyze and look after how a person needs to be handled and what kind of speech one can use. The application is useful for quickly gaining insights using large volumes of data.

2.) Dashboard (web app): The whole data is saved on the server so if a person has consulted by psychiatrist whole data presented to a psychiatrist with a Good-Visualization.
for this, we have developed a Dashboard where psychiatrists can see records of patients using a unique key provided by the patient.

Challenges we ran into

Problems:
1.) while building ML model due to data collection
2.) While making Restful API

3. While deploying Restful API
4. While connecting the app with API
   Crossed hurdle by Scrapping the web data and reading google scholar research papers, learning from various online tutorials, and googling stuff