Sound Like a TEDx Speaker is an application that takes a user story, meshes it together with the content of one of the three most popular TED speakers and generates new text for user to use.
Why I chose to do it?
It roughly takes two to three months to prepare a TEDx Talk: from initial conversation, to drafting proposal, to countless numbers of Google hangouts until a speaker can hold a final up to 18min talk text in her hands. Such intense preparation is necessary to not only have a text to say on the stage, but to have a story where place of every word makes sense.
Which TED speakers?
3 most viewed TED speakers: Ken Robinson, Amy Cuddy and Simon Sinek.
Version1: is done using RiTa.js library and RiTa.getPosTags function, which means that every time user inputs her story, RiTa.js library will divide it by parts of speech and then will replace them accordingly with parts of speech from one of the speakers’ talk.
Documentation: Github repo.
Version2: is done using Markov chain generator. After user submits her story, it is meshed together with a selected TED Talk text and using n-grams and Markov chain algorithm new talk is generated.
Documentation: Github repo.
Why I chose to do it?
It roughly takes two to three months to prepare a TEDx Talk: from initial conversation, to drafting proposal, to countless numbers of Google hangouts until a speaker can hold a final up to 18min talk text in her hands. Such intense preparation is necessary to not only have a text to say on the stage, but to have a story where place of every word makes sense.
Which TED speakers?
3 most viewed TED speakers: Ken Robinson, Amy Cuddy and Simon Sinek.
Version1: is done using RiTa.js library and RiTa.getPosTags function, which means that every time user inputs her story, RiTa.js library will divide it by parts of speech and then will replace them accordingly with parts of speech from one of the speakers’ talk.
Documentation: Github repo.
Version2: is done using Markov chain generator. After user submits her story, it is meshed together with a selected TED Talk text and using n-grams and Markov chain algorithm new talk is generated.
Documentation: Github repo.