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?

Brunato D;Dell'Orletta F;Venturi G
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
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Inglese
Conference on Empirical Methods in Natural Language Processing (EMNLP)
1
10
10
978-1-948087-84-1
https://www.aclweb.org/anthology/D18-1289/
Association for Computational Linguistics
Stroudsburg
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
31/10/2018-04/11/2018
Brussels
Linguistic complexity
Crowdsourcing
Human perception
3
none
Brunato D.; De Mattei L.; Dell'Orletta F.; Iavarone B.; Venturi G.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/371346
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