What does a poem look like?

Poemage is a data visualization tool that lets poets “see” their work. The tool runs off data derived from a poem’s “Sonic Topology”, and was developed at the University of Utah through a collaboration between data visualization and poetry experts.

To find out more about Poemage, Enrico Bertini and Moritz Stefaner from Data Stories interviewed Miriah Meyer and Nina McCurdy, two of the researchers behind the project.

Data Stories: What is Sonic Topology?

Nina McCurdy: It’s actually a term that we made up in order to describe the way in which the various sonic devices within a poem interact to form a kind of sonic landscape. And that’s something that our poets are really interested in exploring in a poem - not just exploring the sonic landscape of a poem but how that landscape interacts with the semantics of a poem. So, we’ve created a user interface, a tool that allows them to explore the sonic typology on a poem of their choosing. Basically, they load up the poem and then they can browse through all the different sonic devices that we are detecting within a poem and start to build their own version of the sonic typology that they can explore.

And in principle, you can put any text or any poetic text into the tool and it will automatically draw all these paths?

Nina McCurdy: Yes. So, on the back end, we’re extracting all the pronunciations of the words and then we’re detecting our patterns based on those pronunciations.

Miriah Meyer: Which leads to some really interesting caveats about the poem because of the back end technology that we’re using to basically sonify the poem. The software we’ve developed is based on the CMU Dictionary, which is a large manually curated dictionary of about 160,000 words that someone’s gone in and basically said, “For this word, here are the phonemes that make it up.” But the interesting thing is that dictionary is based on a modern day mid-Atlantic American dialect and one of the things that our poets are constantly saying is like, “Oh, turns out that not all poetry was written for a modern day mid-Atlantic American dialect. Can we do other things?” And so, that’s when things start to get interesting from a natural language processing perspective.

Nina McCurdy: And actually, that brings up another nice point. So, we have our words that are in the dictionary and then, for words that aren’t in the CMU dictionary, we use automated methods. And while we’re making a lot of really good progress in text to speech, we’re still not quite there yet. So, these automated methods will sometimes mispronounce the word. And we thought initially, “Oh, we need to figure out how to reduce this and make sure we’re getting the right pronunciation.” But our poets are actually incredibly excited about the idea of a mispronunciation because maybe that will reveal new insights about the poem. So, that actually gives you a sense of our collaboration in-and-of-itself.

Can you tell us a bit about the functionality of the final design? How can you use the tool and what does it visualize exactly?

Nina McCurdy: Okay. So, I’ll start with describing what it looks like. The interface has three linked views. So, the linked view on the left is this menu where you can browse through different detected rhymes and rhymes we’re using broadly. You can scroll over these little circles and it highlights, in a different linked view, it highlights these different paths that I mentioned earlier meandering through the space of the poem.


The linked view in the centre shows the text of the poem, and this was something that was really important to our collaborators. They really wanted to preserve the text. They wanted to always be able to see the text and the shape of the poem and be able to go back to that and explore via the text. So, the centre is the poem view and there are several different interactions that they can do in there. And then, on the right is the path view. So, that presents an abstracted view of the poem where you have nodes that represent the words and then, you have these paths that connect the different sets, the rhyme sets.

So can you tell us a little bit more about reactions from the poets and what they have been able to do?

Nina McCurdy: Yeah. So, one little anecdote that we really like because we think it’s particularly revealing happened when one of our poets was looking at the poem “This Is Just To Say” by William Carlos Williams.

I have eaten
the plums
that were in
the icebox

and which
you were probably
for breakfast

forgive me
they were delicious
so sweet
and so cold

And so, she was exploring this poem and she touched on one of the features which we call Beautiful Mess, which highlights all the rhymes sets for a given poem, and what she found was that the only word that wasn’t participating in any of the sonic patterns was the word “You.” And the poem as you heard, is an apology to “You,” the reader. So, the fact that there is this isolated sound, “You” this isolated word, was really pretty significant and it was something that they felt they couldn't have found otherwise.

If you look back now on the project, what are your main takeaways? And if you were to start fresh, would you do the same thing again or would you at some point say, “Ah, we should have taken that avenue!” or if you do maybe something new with music or so, how is the project changed?

Miriah Meyer: That’s a really really great question. And I think for me at least, it really… it caused me to be more open to things that the collaborators say that they want or want to suggest. I feel like a lot of the time, I’ve been in situations where people are like, “Oh but I love the red to green colormap” and I’m like “No, no, no, no! Not good!” And in this poetry project though, there was a lot of things around visual clutter, around ambiguity, that kind of turned a lot of the visual conventions that we use on its head. So, I feel like I’m hoping to be more receptive to these sort of things going forward.

Nina McCurdy: Well, I think that in terms of starting a new project like this, I think that one thing that was really valuable in the beginning was getting to know the dialogue going on in the digital humanities and this question of “What is the role of technology in the digital humanities and our community?” and being really sensitive to that. That led us away from solving the poem to much more radical things that we had a lot of fun with. And then, also this idea of creating a research environment that reflected our collaborators’ research environment. So, they’re very playful and exploratory and experimental in their research and I think mimicking that and exploring the visualization in that way was also really helpful in getting things started.

Miriah Meyer: And I think even… beyond visualization, just thinking about computer science, I think a lot of people in the field are trying to think about, “Well, what does computing means as we go forward?” when computers, you know, they’re impacting everything about our lives. It’s not just about data analysis and trying to really get a handle on well, what does this mean for the future of computer science? For me, this project was a really great peek into – well, there are all these people in fields very far away from us that are interested or using technology. How do we start to think about working with them? How do we start thinking about the value of computation in that space? And it’s still something that I struggle with because I’m an engineer and I like to solve things. And so, it takes me out of my comfort zone. But I do think that this kind of thing is something that’s going to be coming up more and more.

Download Poemage here.

This piece is an edited version of an interview that was originally broadcast on the Data Stories podcast by Enrico Bertini and Moritz Stefaner. Listen to the full podcast here.