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My wife, Monica, questioned my retelling of why we left Chicago. Trees and access to nature were part of it, but surely there were trees in Chicago. Humboldt Park has a few, and so does Grant Park, maybe. No more than a light peppering, though. Never enough to enter into a clump of them, to turn around and see them guarding your path back.

Chicago has its share of other problems, with corruption and shootings, a despicable waste management stream, a winter wind that will race through the streets and slice you in two. But it also has an earnestness and community, a muffled unity against the cold, phenomenal Mexican food, the best public transit system (until NYC works out those ceaseless delays, if ever), amazing architecture and pale copies of that architecture, really lovely people, among a million other things.

We’ll probably move back in a year or two.

(I wrote this last night on my phone, so I haven’t broken the streak.)

I realized that the best first step, the begin, is to research topics in the NLP space. This involves reading papers, which I’ll start outlining here:

Phonemic Similarity Metrics to Compare Pronunciation Methods
This paper outlines a novel algorithm to score the similarity of pronunciations that based partly on how biologists compare protein sequences. A score is calculated based on the length and phonemes in the word, and the number of blank entries inserted to achieve that alignment. They also leverage the alternate pronunciations for words in the CMUDict, splitting out their different phonemes and use that as a basis for what should be considered similar.