Inflection Generation for Spanish Verbs using Supervised Learning

Barros, Cristina; Gkatzia, Dimitra; Lloret, Elena

Abstract

We present a novel supervised approach to inflection generation for verbs in Spanish. Our system takes as input the verb’s lemma form and the desired features such as person, number, tense, and is able to predict the appropriate grammatical conjugation. Even though our approach learns from fewer examples comparing to previous work, it is able to deal with all the Spanish moods (indicative, subjunctive and imperative) in contrast to previous work which only focuses on indicative and subjunctive moods. We show that in an intrinsic evaluation, our system achieves 99% accuracy, outperforming (although not significantly) two competitive state-of-art systems. The successful results obtained clearly indicate that our approach could be integrated into wider approaches related to text generation in Spanish.

Citation

Barros, C., Gkatzia, D., & Lloret, E. (2017, September). Inflection Generation for Spanish Verbs using Supervised Learning. Presented at First Workshop on Subword and Character Level Models in NLP, Copenhagen, Denmark

• Presentation Conference Type: Conference Paper (published)
• Conference Name: First Workshop on Subword and Character Level Models in NLP
• 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: 136-141
• Book Title: Proceedings of the First Workshop on Subword and Character Level Models in NLP
• DOI: https://doi.org/10.18653/v1/W17-4120
• Public URL: http://researchrepository.napier.ac.uk/Output/2658035
• Publisher URL: https://www.aclweb.org/anthology/W17-4120