Conference article

Looking hard: Eye tracking for detecting grammaticality of automatically compressed sentences

Sigrid Klerke
University of Copenhagen, Copenhagen, Denmark

Héctor Martínez Alonso
University of Copenhagen, Copenhagen, Denmark

Anders Søgaard
University of Copenhagen, Copenhagen, Denmark

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Published in: Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania

Linköping Electronic Conference Proceedings 109:14, s. 97-105

NEALT Proceedings Series 23:14, s. 97-105

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Published: 2015-05-06

ISBN: 978-91-7519-098-3

ISSN: 1650-3686 (print), 1650-3740 (online)


Natural language processing (NLP) tools are often developed with the intention to ease human processing, a goal which is hard to measure. Eye movements in reading are known to reflect aspects of the cognitive processing of text (Rayner et al., 2013) and is becoming available in consumer products. We explore how eye movements reflect aspects of reading that are of relevance to NLP system evaluation and development. In this paper we present an analysis of the differences between reading automatic sentence compressions and manually simplified newswire using eye-tracking experiments and readers’ evaluations. We show that both manual simplification and automatic sentence compression provide texts that are easier to process than standard newswire, and that the main source of difficulty in processing machine-compressed text is ungrammaticality. Importantly, we find that grammatical errors introduced by automatic processing and grammatical complexity stemming from human authors affects reading behavior and the subjective assessment of sentence readability differently. Especially the proportion of regressions to previously read text is found to be sensitive to the differences in human- and computer-induced complexity. This finding is relevant for evaluation of automatic summarization, simplification and translation systems designed with the intention of facilitating human reading.


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