Bilingual Lexicon Induction From Comparable and Parallel Data: A Comparative Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F24%3A00136956" target="_blank" >RIV/00216224:14330/24:00136956 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-70563-2_3" target="_blank" >http://dx.doi.org/10.1007/978-3-031-70563-2_3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-70563-2_3" target="_blank" >10.1007/978-3-031-70563-2_3</a>
Alternative languages
Result language
angličtina
Original language name
Bilingual Lexicon Induction From Comparable and Parallel Data: A Comparative Analysis
Original language description
Bilingual lexicon induction (BLI) from comparable data has become a common way of evaluating cross-lingual word embeddings (CWEs). These models have drawn much attention, mainly due to their availability for rare and low-resource language pairs. An alternative offers systems exploiting parallel data, such as popular neural machine translation systems (NMTSs), which are effective and yield state-of-the-art results. Despite the significant advancements in NMTSs, their effectiveness in the BLI task compared to the models using comparable data remains underexplored. In this paper, we provide a comparative study of the NMTS and CWE models evaluated on the BLI task and demonstrate the results across three diverse language pairs: distant (Estonian-English) and close (Estonian-Finnish) language pair and language pair with different scripts (Estonian-Russian). Our study reveals the differences, strengths, and limitations of both approaches. We show that while NMTSs achieve impressive results for languages with a great amount of training data available, CWEs emerge as a better option when faced less resources.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
International Conference on Text, Speech, and Dialogue
ISBN
9783031705625
ISSN
0302-9743
e-ISSN
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Number of pages
13
Pages from-to
30-42
Publisher name
Springer Nature Switzerland
Place of publication
Cham
Event location
Cham
Event date
Jan 1, 2024
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
001307840300003