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        <title>Keystroke dynamics as signal for shallow syntactic parsing</title>
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    <name type="personal">
        <namePart type="given">Barbara</namePart>
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            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
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        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
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    <abstract>Keystroke dynamics have been extensively used in psycholinguistic and writing research to gain insights into cognitive processing. But do keystroke logs contain actual signal that can be used to learn better natural language processing models? We postulate that keystroke dynamics contain information about syntactic structure that can inform shallow syntactic parsing. To test this hypothesis, we explore labels derived from keystroke logs as auxiliary task in a multi-task bidirectional Long Short-Term Memory (bi-LSTM). Our results show promising results on two shallow syntactic parsing tasks, chunking and CCG supertagging. Our model is simple, has the advantage that data can come from distinct sources, and produces models that are significantly better than models trained on the text annotations alone.</abstract>
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        <url>https://aclanthology.org/C16-1059</url>
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%0 Conference Proceedings
%T Keystroke dynamics as signal for shallow syntactic parsing
%A Plank, Barbara
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F plank-2016-keystroke
%X Keystroke dynamics have been extensively used in psycholinguistic and writing research to gain insights into cognitive processing. But do keystroke logs contain actual signal that can be used to learn better natural language processing models? We postulate that keystroke dynamics contain information about syntactic structure that can inform shallow syntactic parsing. To test this hypothesis, we explore labels derived from keystroke logs as auxiliary task in a multi-task bidirectional Long Short-Term Memory (bi-LSTM). Our results show promising results on two shallow syntactic parsing tasks, chunking and CCG supertagging. Our model is simple, has the advantage that data can come from distinct sources, and produces models that are significantly better than models trained on the text annotations alone.
%U https://aclanthology.org/C16-1059
%P 609-619

Markdown (Informal)

[Keystroke dynamics as signal for shallow syntactic parsing](https://aclanthology.org/C16-1059) (Plank, COLING 2016)

• Keystroke dynamics as signal for shallow syntactic parsing (Plank, COLING 2016)

ACL

• Barbara Plank. 2016. Keystroke dynamics as signal for shallow syntactic parsing. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 609–619, Osaka, Japan. The COLING 2016 Organizing Committee.