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Random fun with statistical language models.
This project forked from darius/languagetoys
Random fun with statistical language models.
Currently here: a Markov random sonnet generator. There's sample output at http://darius.livejournal.com/47444.html (The program does somewhat better now than what's shown off there.) To generate it: $ python verse.py sonnet # or limerick or other verse form it knows about Currently missing: the data it works from. You need two files: * 2gm-common6: from http://norvig.com/ngrams/ (lines like "word1 word2\tcount" for common bigrams) (word1 can be "<S>" for start of sentence) * cmudict.0.7a: from http://www.speech.cs.cmu.edu/cgi-bin/cmudict I'd like to add I don't normally publish code in such a crap state. Some other hacks thrown in here: * anagram.py generates multiword anagrams * bestpermutation.py helps to sort anagrams by quality (using n-gram statistics and brute force) * bibleanalyze.py breaks down the Gutenberg Project's KJ Bible into raw material for other hacks here * companynames.py generate random Web2.0 company names, along with a plausibility rating for each. * emvowel.py reverses disemvoweling * mnemonify.py tries to invent mnemonics like pi's "How I wish I could enumerate pi easily..." * portmanteau.py finds pairs of words that blend nicely, like book + hookup --> bookup * summarize.py generates chapter 'summaries' for a book, like http://wry.me/blog/2010/04/08/quantitative-tolkien-studies.html * textanalyze.py is a super-crude sentence segmenter * tohtml.py writes HTML that highlights words with increasing intensity the more unlikely they are according to a language model * verse.py described above See also https://github.com/darius/amphigory for verse-making rewritten in Javascript.
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