V^2: Virtual Voice for Autistic Students
Having seen my nephew struggle with understanding how to best interact with fellow students as an autistic student, I took on the challenge of creating a platform to further the education of sentiment analysis for autistic students around the world. Currently, understanding how one's intent in speech is delivered is analyzed in limited capacities and environments. With V^2, any student with a long curve to learning social interactions through speech can analyze their written work and diary entries to best understand how to apply strategies recommended by their academic and psychological facilitators.
Tools Used
To implement this, we created a backend and front-end of the web app using Node.js, HTML5, JavaScript, React.js, and chart.js for visualization and mapping of the sentiment. We used the Google Cloud Natural Language Processing API to analyze sentiment scores over the provided text.
What We Learned
We learned how to use the Google Cloud NLP API, how to analyze and rank sentiment, and how to build a React app.
Challenges Faced
We faced some challenges with implementing the Google Cloud NLP API because it required pre-setup in Google Cloud, and its syntax in Node.js had to be modified for our React.js backend.
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