Language Adaptation (similarly to Domain Adaptation) is a general approach to extend existing resources from a better resourced language (donor) to a lesser resourced one (recipient) by exploiting the lexical and grammatical similarity between them when the two languages are related. The current study improves the state of the art in cross-lingual word embeddings by considering the impact of orthographic similarity between cognates. In particular, the use of the Weighted Levenshtein Distance combined with orthogonalisation of the translation matrix and generalised correction for hubness can considerably improve the state of the art in induction of bilingual lexicons. In addition to intrinsic evaluation in the bilingual lexicon induction task, the paper reports extrinsic evaluation of the cross-lingual embeddings via their application to the Named-Entity Recognition task across Slavonic languages. The tools and the aligned word embedding spaces for the Romance and Slavonic language families have been released.
@InProceedings{SHAROFF18.227, author = {Serge Sharoff}, title = "{Language adaptation experiments via cross-lingual embeddings for related languages}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
Summary of the paper