UMUTextStats: A linguistic feature extraction tool for Spanish
José Antonio García-Díaz, Pedro José Vivancos-Vicente, Ángela Almela, Rafael Valencia-García
Abstract
Feature Engineering consists in the application of domain knowledge to select and transform relevant features to build efficient machine learning models. In the Natural Language Processing field, the state of the art concerning automatic document classification tasks relies on word and sentence embeddings built upon deep learning models based on transformers that have outperformed the competition in several tasks. However, the models built from these embeddings are usually difficult to interpret. On the contrary, linguistic features are easy to understand, they result in simpler models, and they usually achieve encouraging results. Moreover, both linguistic features and embeddings can be combined with different strategies which result in more reliable machine-learning models. The de facto tool for extracting linguistic features in Spanish is LIWC. However, this software does not consider specific linguistic phenomena of Spanish such as grammatical gender and lacks certain verb tenses. In order to solve these drawbacks, we have developed UMUTextStats, a linguistic extraction tool designed from scratch for Spanish. Furthermore, this tool has been validated to conduct different experiments in areas such as infodemiology, hate-speech detection, author profiling, authorship verification, humour or irony detection, among others. The results indicate that the combination of linguistic features and embeddings based on transformers are beneficial in automatic document classification.- Anthology ID:
- 2022.lrec-1.649
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 6035–6044
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.649
- DOI:
- Cite (ACL):
- José Antonio García-Díaz, Pedro José Vivancos-Vicente, Ángela Almela, and Rafael Valencia-García. 2022. UMUTextStats: A linguistic feature extraction tool for Spanish. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6035–6044, Marseille, France. European Language Resources Association.
- Cite (Informal):
- UMUTextStats: A linguistic feature extraction tool for Spanish (García-Díaz et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.lrec-1.649.pdf