Pavel Rychlý

Michaela Denisová

Cross-lingual embedding models (CMs) enable us to transfer lexical knowledge across languages. Therefore, they represent a useful approach for retrieving translation equivalents in lexicography. However, these models have been mainly oriented towards the natural language processing (NLP) field, lacking proper evaluation with error evaluation datasets that were compiled automatically. This causes discrepancies between models hindering the correct interpretation of the results. In this paper, we aim to address these issues and make these models more accessible for lexicography by evaluating them from a lexicographic point of view. We evaluate three benchmark CMs on three diverse language pairs: close, distant, and different script languages. Additionally, we propose key parameters that the evaluation dataset should include to meet lexicographic needs, have reproducible results, accurately reflect the performance, and set appropriate parameters during training. Our code and evaluation datasets are publicly available.

Evaluation of the Cross-lingual Embedding Models from the Lexicographic Perspective

Aleš Horák

Klára Osolsobě

Dana Hlaváčková

The book contains 25 chapters by leading experts in the area of computer processing of Slavonic natural languages. It focuses on the advances in Slavonic natural language processing in the second half of the 20th century. The whole book was dedicated to Karel Pala.

After Half a Century of Slavonic Natural Language Processing

Adam Rambousek

The book reflects new advances in Slavonic natural language processing at the beginning of the 21th century. The whole book was dedicated to Karel Pala.

Pavel Rychlý

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