Kernel Least Squares Transformations for Cross-lingual Semantic Spaces
Text, Speech, and Dialogue (2024)
Abstract
The rapid development in the field of natural language processing (NLP) and the increasing complexity of linguistic tasks demand the use of efficient and effective methods. Cross-lingual linear transformations between semantic spaces play a crucial role in this domain. However, compared to more advanced models such as transformers, linear transformations often fall short, especially in terms of accuracy. It is thus necessary to employ innovative approaches that not only enhance performance but also maintain low computational complexity. In this study, we propose Kernel Least Squares (KLS) for linear transformation between semantic spaces. In our comprehensive analysis involving three intrinsic and two extrinsic experiments across six languages from three different language families and a comparative evaluation with nine different linear transformation methods, we demonstrate the superior performance of KLS. Our results show that the proposed method significantly improves word translation accuracy, thereby standing out as the most efficient method for transforming only the source semantic space.
Authors
BibTex
@InProceedings{10.1007/978-3-031-70563-2_18, author="Mi{\v{s}}tera, Adam and Brychc{\'i}n, Tom{\'a}{\v{s}}", editor="N{\"o}th, Elmar and Hor{\'a}k, Ale{\v{s}} and Sojka, Petr", title="Kernel Least Squares Transformations for Cross-Lingual Semantic Spaces", booktitle="Text, Speech, and Dialogue", year="2024", publisher="Springer Nature Switzerland", address="Cham", pages="227--238", abstract="The rapid development in the field of natural language processing (NLP) and the increasing complexity of linguistic tasks demand the use of efficient and effective methods. Cross-lingual linear transformations between semantic spaces play a crucial role in this domain. However, compared to more advanced models such as transformers, linear transformations often fall short, especially in terms of accuracy. It is thus necessary to employ innovative approaches that not only enhance performance but also maintain low computational complexity.", isbn="978-3-031-70563-2" }
