6533b853fe1ef96bd12ad73e
RESEARCH PRODUCT
Monolingual and cross-lingual intent detection without training data in target languages
Askars SalimbajevsRaivis SkadiņšJurgita Kapočiūtė-dzikienėsubject
Machine translationTK7800-8360Computer Networks and CommunicationsComputer sciencePT languages0211 other engineering and technologies02 engineering and technologycomputer.software_genre[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]DEGermanFRLTLV0202 electrical engineering electronic engineering information engineeringEN DE FR LT LV PT languagesmonolingual and cross-lingual experimentsElectrical and Electronic Engineering021110 strategic defence & security studiesbusiness.industryCosine similarityLatvian020206 networking & telecommunicationsLithuanianEager learningword and sentence transformerslanguage.human_languageLazy learningHardware and ArchitectureControl and Systems EngineeringSignal ProcessinglanguageENArtificial intelligenceElectronicsbusinesscomputerSentenceNatural language processingBERTdescription
Due to recent DNN advancements, many NLP problems can be effectively solved using transformer-based models and supervised data. Unfortunately, such data is not available in some languages. This research is based on assumptions that (1) training data can be obtained by the machine translating it from another language
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-06-11 |