Distinguishing Voices in The Waste Land using Computational Stylistics

Julian Brooke, Adam Hammond, Graeme Hirst


Abstract
T. S. Eliot’s poem The Waste Land is a notoriously challenging example of modernist poetry, mixing the independent viewpoints of over ten distinct characters without any clear demarcation of which voice is speaking when. In this work, we apply unsupervised techniques in computational stylistics to distinguish the particular styles of these voices, offering a computer’s perspective on longstanding debates in literary analysis. Our work includes a model for stylistic segmentation that looks for points of maximum stylistic variation, a k-means clustering model for detecting non-contiguous speech from the same voice, and a stylistic profiling approach which makes use of lexical resources built from a much larger collection of literary texts. Evaluating using an expert interpretation, we show clear progress in distinguishing the voices of The Waste Land as compared to appropriate baselines, and we also offer quantitative evidence both for and against that particular interpretation.
Anthology ID:
2015.lilt-12.2
Volume:
Linguistic Issues in Language Technology, Volume 12, 2015 - Literature Lifts up Computational Linguistics
Month:
Oct
Year:
2015
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LILT
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CSLI Publications
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URL:
https://aclanthology.org/2015.lilt-12.2
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Cite (ACL):
Julian Brooke, Adam Hammond, and Graeme Hirst. 2015. Distinguishing Voices in The Waste Land using Computational Stylistics. In Linguistic Issues in Language Technology, Volume 12, 2015 - Literature Lifts up Computational Linguistics. CSLI Publications.
Cite (Informal):
Distinguishing Voices in The Waste Land using Computational Stylistics (Brooke et al., LILT 2015)
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PDF:
https://aclanthology.org/2015.lilt-12.2.pdf