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Monolingual and Cross-Lingual Intent Detection without Training Data in Target Languages
2021
Electronics
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; (2) there are cross-lingual solutions that work without the training data in the target language. Consequently, in this research, we use the English dataset and solve the intent
doi:10.3390/electronics10121412
fatcat:tjwfqbmimnghzecwy4jh72bvja