In this paper, we present a crowdsourcing-based approach to model the human perception of sentence complexity. We collect a large corpus of sentences rated with judgments of complexity for two typologically-different languages, Italian and English. We test our approach in two experimental scenarios aimed to investigate the contribution of a wide set of lexical, morpho-syntactic and syntactic phenomena in predicting i) the degree of agreement among annotators independently from the assigned judgment and ii) the perception of sentence complexity.

Is this sentence difficult? Do you agree?

Iavarone, Benedetta;
2018

Abstract

In this paper, we present a crowdsourcing-based approach to model the human perception of sentence complexity. We collect a large corpus of sentences rated with judgments of complexity for two typologically-different languages, Italian and English. We test our approach in two experimental scenarios aimed to investigate the contribution of a wide set of lexical, morpho-syntactic and syntactic phenomena in predicting i) the degree of agreement among annotators independently from the assigned judgment and ii) the perception of sentence complexity.
2018
Settore INF/01 - Informatica
2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
bel
2018
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
Association for Computational Linguistics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/134285
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