This project explores the use of a generative adversarial network to produce Bananagrams boards given a starting hand.
Several English dictionaries of "common" words were combined to generate a dictionary of acceptable words. These include:
- Lists from https://people.sc.fsu.edu/~jburkardt/datasets/words/words.html under the LGPL license:
- basic_english_850.txt
- basic_english_2000.txt
- doublet_words.txt
- globish.txt
- simplified_english.txt
- special_english.txt
- unique_grams.txt
- Lists from /~https://github.com/MichaelWehar/Public-Domain-Word-Lists in the public domain:
- 200-less-common.txt
- 5000-more-common.txt
- MIT's 10000 word list (https://www.mit.edu/~ecprice/wordlist.10000)
- wordlist.10000.txt
- 10000 word list derived from Google (/~https://github.com/first20hours/google-10000-english)
- google-10000-english.txt
The base dictionary was short_dictionary.txt from a previous Bananagrams solver project of mine. I combined that dictionary with the ones listed here using combine_dictionary.ipynb to form new_short_dictionary.txt; some manual editing was performed as well.
All source dictionary text files are stored in dictionaries.tar.gz, and the derived one is present in the repository root.