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Semantic mapping of natural language input to database entries via convolutional neural networks.

, , and . ICASSP, page 5685-5689. IEEE, (2017)

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Corpus for Customer Purchase Behavior Prediction in Social Media., , , and . LREC, European Language Resources Association (ELRA), (2016)Spoken Language Understanding for a Nutrition Dialogue System., and . IEEE ACM Trans. Audio Speech Lang. Process., 25 (7): 1450-1461 (2017)Dialogue State Tracking with Convolutional Semantic Taggers., and . ICASSP, page 7220-7224. IEEE, (2019)Deep learning for spoken dialogue systems: application to nutrition.. Massachusetts Institute of Technology, Cambridge, USA, (2019)ndltd.org (oai:dspace.mit.edu:1721.1/122557).A New Dataset for Natural Language Understanding of Exercise Logs in a Food and Fitness Spoken Dialogue System., , and . SLT, page 1071-1078. IEEE, (2021)Deep Learning for Database Mapping and Asking Clarification Questions in Dialogue Systems., and . IEEE ACM Trans. Audio Speech Lang. Process., 27 (8): 1321-1334 (2019)Convolutional Neural Networks and Multitask Strategies for Semantic Mapping of Natural Language Input to a Structured Database., and . ICASSP, page 6174-6178. IEEE, (2018)Convolutional Neural Networks for Dialogue State Tracking without Pre-Trained Word Vectors or Semantic Dictionaries., and . SLT, page 884-891. IEEE, (2018)Semantic mapping of natural language input to database entries via convolutional neural networks., , and . ICASSP, page 5685-5689. IEEE, (2017)Character-Based Embedding Models and Reranking Strategies for Understanding Natural Language Meal Descriptions., , and . INTERSPEECH, page 3320-3324. ISCA, (2017)