Thursday, April 14, 2011

Pre-Meeting Alan

Related paper: Using an on-line dictionary to find rhyming words and pronunciation for unknown words
Focus paper: Poetic Statistical Machine Translation: Rhyme and Meter

The related paper I read this week was a little dated, being from ACL 1985. But it was a pretty interesting read, detailing a computer system WordSmith that was being built by IBM at the time. WordSmith is a multi-dimensional dictionary - that is, given an input word, it can display words with similar pronunciation, words that are likely to rhyme with the input word, and words with similar end-spellings. It can also attempt to generate pronunciations of words that do not exist in its dictionary. The main focus of the paper is on the methodology for implementing the system that finds rhymes, and also the system that determines how to pronounce words that the system has not seen before.

Instead of a spelling-based algorithm to identify rhyming words, they use a pronunciation-based approach. There is a three-part encoding scheme that starts of with mapping pronunciation symbols to single-byte codes that represent phonetic segments. The second part of the encoding scheme arranges the word segments in order of importance for determining rhyme. Lastly, the rearranged segments are reversed, grouped based on the position of the primary-stress syllable, and sorted (according to the reversed order) I will skip over the details here, but the only real limitation of their approach is the fundamental disagreement amongst people of what are rhymes are good and not so good.

To try and pronounce an unknown input word, the basic approach is to find overlapping substrings in the input word that are present in words already in the dictionary. Basically it's like a probabilistic version of minimum edit distance. The substrings are chosen greedily in the sense that the chosen substrings are the longest that can be matched in the dictionary file.

Most of the ideas introduced by the paper are interesting and seem like they would do well in a full-fledged system as the one described. There isn't any hard data or experiments to show the progress of the system which may been just a technological limitation at the time. But definitely the paper brings up some psycholinguistic questions about how words can be and are represented.

No comments:

Post a Comment

Note: Only a member of this blog may post a comment.