How it works
Here’s a quick breakdown of how the game works:
- User copy and pastes in a story as a text snippet or uses the built-in search box to search Wikipedia to use as a source story.
- After input is analyzed, user sees a series of word prompts (i.e. adjective, living thing, or location) and enters a corresponding word to fit that criteria.
- User views the final output which utilizes the user’s responses to the aforementioned word prompts to generate a new story
Initial Flow
NLP Algorithm Ideation
In order to identify which words of a given text input we needed to replace, we first needed to understand the word’s role and importance in the sentence. Thus I needed to devise an algorithm that would identify not just a word’s part of speech i.e. noun, verb, adverb, direct object, etc., and salience (i.e. the word entity’s significance to the entire text snippet) using Google’s NLP APIs and also its top-level category (aka synset family) using a JSON file generated from a database compiled by wordnet to generate the replacement prompts.