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Locale-agnostic Universal Domain Classification Model in Spoken Language Understanding.

, , and . NAACL-HLT (2), page 9-15. Association for Computational Linguistics, (2019)

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Task specific continuous word representations for mono and multi-lingual spoken language understanding., , and . ICASSP, page 3246-3250. IEEE, (2014)Frustratingly Easy Neural Domain Adaptation., , and . COLING, page 387-396. ACL, (2016)A Scalable Framework for Learning From Implicit User Feedback to Improve Natural Language Understanding in Large-Scale Conversational AI Systems., , , , , , , and . EMNLP (1), page 6054-6063. Association for Computational Linguistics, (2021)Cross-Lingual Transfer Learning for POS Tagging without Cross-Lingual Resources., , , and . EMNLP, page 2832-2838. Association for Computational Linguistics, (2017)Multi-Player Virtual Ping-Pong Game., , , , and . ICAT, page 269-273. IEEE Computer Society, (2007)An overview of end-to-end language understanding and dialog management for personal digital assistants., , , , , , , , , and 8 other author(s). SLT, page 391-397. IEEE, (2016)Locale-agnostic Universal Domain Classification Model in Spoken Language Understanding., , and . NAACL-HLT (2), page 9-15. Association for Computational Linguistics, (2019)Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents., , , and . NAACL-HLT, page 4053-4064. Association for Computational Linguistics, (2021)Pseudo Labeling and Negative Feedback Learning for Large-Scale Multi-Label Domain Classification., and . ICASSP, page 7964-7968. IEEE, (2020)A Multi-phase Semi-supersense Tagging of Korean Unknown Nouns., , and . ICHIT (2), volume 310 of Communications in Computer and Information Science, page 760-766. Springer, (2012)