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[WSS19] Computer Analysis of Poetry — Part 2: Rhyme

Posted 6 years ago
POSTED BY: Mark Greenberg
7 Replies

A rap that rhymes rapping with wrapping is fair game no rapper would rip. But to rhyme rapping with...rapping? That's a trap no rapper would trip. While I might be wily, I'd not be unruly, if I rhymed while I wrote why I'm rapt.

POSTED BY: Daniel Lichtblau
Posted 4 years ago

Yes, clever. But if we're talking about sounds, how is rap/wrap rhyme while rap/rap isn't? Another question... We use imperfect rhyme (slant rhyme) so much in modern song and verse, isn't telling a computer to search for words that rhyme, like dog and log, missing half the rhymes? I'm leaning toward identifying phoneme echoes. True rhymes will show heavy phoneme echoes, while slant rhyme will show some. Weighting the phoneme echoes by whether they're in a stressed or unstressed syllable brings this out even more. Off-beat rhymes are subtle.

POSTED BY: Mark Greenberg

"We use imperfect rhyme (slant rhyme) so much in modern song and verse"

Reminds me of a stanza from Tom Lehrer's "The Folksong Army". Funny..I just now looked it up to get an appropriate link.

https://www.google.com/search?channel=fs&client=ubuntu&q=The+Folksong+Army

The Youtube hit actually shows the punchline, so to speak, for that particular verse.

POSTED BY: Daniel Lichtblau

This is very interesting! If you might be interested in somewhat traditional publication, Journal of Humanistic Mathematics could be a good possible outlet for this kind of work. (I am one of the editors. And no, I don't spam everyone's content page to get submissions. This really looked interesting! In particular I'd love to know what motivated you to get into this project and what kinds of teaching uses you can envision.)

I was intrigued by your sentence: "The point is that the computer can detect features in poetry and visualize them." For me, this brings up interesting questions about poetry and its humanity. Can a computer that is aware of these poetic features eventually create "good poetry" (whatever that might mean)? Maybe a future project?

POSTED BY: Gizem Karaali
Posted 4 years ago

The Wolfram Language has the means to analyze a poem for such things as meter, rhyme, and cadence. The project above is proof that this can be done. I have recently started rewriting the project to improve it and remove its reliance on custom neural networks (because I don't have the skill to manage them).

If we could drop a stanza into a computer and have it show us the rhythms, echoes, and pauses, then we could see a large part of the craft that went into making the verse (some more than others). Often the little bits of instruction we give to students about rhyme schemes and meter leave them with the impression that writing poetry is like making waffles because the poet has to somehow pour words into a preexisting mould. Having a visualization would allow students to see that the beat and the echoes come from the words themselves, and that the poet is creating the patterns, not following them.

Thanks, Gizem, for making me aware of the Journal of Humanistic Mathematics. In a few months I should be finishing up the current iteration of the project. I'll consider submitting an article at that time.

POSTED BY: Mark Greenberg
Posted 6 years ago

For those of you taking a close look at the diagrams, you may notice that the code links some rhymes most people would not consider rhymes. There are three main reasons for this. First, it counts repetition as rhyme, so "dog" rhymes with "dog." Second, the algorithm for splitting syllables is not consistent, which leads to some unexpected connections. Finally, we hear rhymes anchored to stressed syllables, while the code is linking echoes from any syllables, stressed or not. I am working toward a better version that will account for these factors. The current code is my project from the Wolfram Summer School. As such, it is richer than it would have been, including ideas from many people, but it also had to be published before I smoothed all the rough edges.

POSTED BY: Mark Greenberg

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