Text analysis for note taking app

So for UNICEF class we decided to make a voice-text note taking app. The uses of such an app are self-evident but our inspiration in particular was the researchers who work for non-profits and do a lot of field interviews. Their workflow would be vastly improved with an app that can convert voice to text and if possible break it down for easier consumption.

I am handling the text analysis part, my teammate is handling the voice to text conversion across more than one language. Now text analysis is a huge field in itself. Depending on how sophisticated you want to get you can make products ranging from simple word counters to AI based assistants. We want to touch a middle ground. Keeping our skills and time at hand in mind, we decided to work on two features:

  1. Generating a summary of the text.
  2. Word frequency, Parts of Speech analysis
Github
https://github.com/kshivanku/textSummary
Tech Used
Demo Screenshots

Sample text is read from a file. I am assuming that voice-text conversion will produce a file like this. This text is from Steve Jobs’ famous commencement speech at Harvard.

 

the algorithm has produced what it thinks is the most important sentence in the speech. Along with that a longer summary is also produced.

 

parts of speech analysis on the text helps in identifying key topics, ideas, feelings etc

 

pronouns

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