Improving the Naturalness and Expressivity of Language Generation for Spanish

Barros, Cristina; Gkatzia, Dimitra; Lloret, Elena

Abstract

We present a flexible Natural Language Generation approach for Spanish, focused on the surface realisation stage, which integrates an inflection module in order to improve the naturalness and expressivity of the generated language. This inflection module inflects the verbs using an ensemble of trainable algorithms whereas the other types of words (e.g. nouns, determiners, etc) are inflected using hand-crafted rules. We show that our approach achieves 2% higher accuracy than two state-of-art inflection generation approaches. Furthermore, our proposed approach also predicts an extra feature: the inflection of the imperative mood, which was not taken into account by previous work. We also present a user evaluation, where we demonstrate that the proposed method significantly improves the perceived naturalness of the generated language.

Citation

Barros, C., Gkatzia, D., & Lloret, E. (2017, September). Improving the Naturalness and Expressivity of Language Generation for Spanish. Presented at 10th International Conference on Natural Language Generation, Santiago de Compostela, Spain

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th International Conference on Natural Language Generation
• Acceptance Date: May 1, 2017
• Publication Date: 2017
• Deposit Date: May 3, 2020
• Publicly Available Date: May 4, 2020
• Publisher: Association for Computational Linguistics (ACL)
• Pages: 41-50
• Book Title: Proceedings of the 10th International Conference on Natural Language Generation
• DOI: https://doi.org/10.18653/v1/W17-3505
• Public URL: http://researchrepository.napier.ac.uk/Output/2658029
• Publisher URL: https://www.aclweb.org/anthology/W17-3505