CMUDaaN

CMU Dictionary as a Network (CMUDaaN) is a lightweight library that reframes the CMU Dictionary as network consisting of weighted edges by proportional matching and words as nodes.

How it works

Each word given by the CMU Dict is broken down into syllables. In Pythonic terms, for each word, there is a list of syllables that represent that word. Therefore, for n words, we now have (n * n-1) / 2 combinations without replacement of words to be studied against using similarity metrics. The metric chosen for this was Jaro Similarity since this produced a number between 0 and 1 and made relative sense with respect to this topic.

Examples

graph_random(...)

Using the function graph(n = 10, show = True), you can create a network like the following:

This selects 10 random words and establishes connections to them through Jaro Similarity. If the similarity is 0, no connection is made.

graph_wordlist(...)

Using the following code:

wordlist = ['hi', 'high', 'height']
g = graph_wordlist(wordlist = wordlist, n = 4, communities = True, show = True)

you obtain the following graph:

graph_synonym(...)

Using the following code:

word = 'dog'
g = graph_synonym(word, communities=True, n_synonyms=None, n = 4, show = True)

you obtain the following graph: