Linear Transformations for Cross-lingual Sentiment Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43965947" target="_blank" >RIV/49777513:23520/22:43965947 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-16270-1_11" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-16270-1_11</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-16270-1_11" target="_blank" >10.1007/978-3-031-16270-1_11</a>
Alternative languages
Result language
angličtina
Original language name
Linear Transformations for Cross-lingual Sentiment Analysis
Original language description
This paper deals with cross-lingual sentiment analysis in Czech, English and French languages. We perform zero-shot cross-lingual classification using five linear transformations combined with LSTM and CNN based classifiers. We compare the performance of the individual transformations, and in addition, we confront the transformation-based approach with existing state-of-the-art BERT-like models. We show that the pre-trained embeddings from the target domain are crucial to improving the cross-lingual classification results, unlike in the monolingual classification, where the effect is not so distinctive.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Text, Speech, and Dialogue, 25th International Conference, TSD 2022, Brno, Czech Republic, September 6–9, 2022, Proceedings
ISBN
978-3-031-16269-5
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
13
Pages from-to
125-137
Publisher name
Springer
Place of publication
Cham
Event location
Brno
Event date
Sep 6, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000866222300011