Part of Speech Tagging and HMM’s
I thought it might be appropriate to begin this posting on Hidden Markov Models and POS with the above video… I came home last night to find my roommate watching this on YouTube. A live concert of Hatsune Miku a synthetic Japanese idol developed from Yamaha’s Vocaloid software. The software offers an interface for building synthesized vocal lyrics from text. I’ve used various versions of the software in the past and found the interpretation of direct text dictionary without using the custom phonology characters to be quite impressive. In any case it’s amazing to see a crowd of people so immersed in a rear projection of an animated character. In this case a fan base and mythology created entirely from TTS. …I felt a nice vignette after witnessing Watson’s victory a few weeks ago and as we start to think more about language recognition and synthesis… in relative form a milestone achieved not through logic but through an emotive form.
Using POS tagging / HMM’s with text generation
While I was able to tag “War and Peace” from last week with parts of speech with a decent level of accuracy (minus the Russian and French at times)… however, I struggled to integrate this with a language generation model with LingPipe or NLTK. Something I am really interested in doing.
Text Mash Ups (“Paradise Lost” and Lanier’s “You are not a gadget”)