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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Multilingual and Cross-Lingual Intent Detection from Spoken Data ... Gerz, Daniela; Su, Pei-Hao; Kusztos, Razvan. - : arXiv, 2021 BASE Show details 2 Multilingual and Cross-Lingual Intent Detection from Spoken Data ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gerz, Daniela; Kusztos, Razvan. - : Underline Science Inc., 2021 BASE Show details 3 Recurrent Neural Network Language Generation for Dialogue Systems Wen, Tsung-Hsien. - : University of Cambridge, 2018. : Engineering, 2018. : Darwin College, 2018 BASE Show details 4 Counter-fitting Word Vectors to Linguistic Constraints ... Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Thomson, Blaise. - : arXiv, 2016 BASE Show details 5 Neural Belief Tracker: Data-Driven Dialogue State Tracking ... Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Wen, Tsung-Hsien. - : arXiv, 2016 BASE Show details 6 Research data supporting "On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems" Su, Pei-Hao; Gasic, Milica; Mrksic, Nikola. - : University of Cambridge, 2016 BASE Show details 7 Multi-domain Dialog State Tracking using Recurrent Neural Networks ... Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Thomson, Blaise; Gašić, Milica; Su, Pei-Hao; Vandyke, David; Wen, Tsung-Hsien; Young, Steve. - : arXiv, 2015 Abstract: Dialog state tracking is a key component of many modern dialog systems, most of which are designed with a single, well-defined domain in mind. This paper shows that dialog data drawn from different dialog domains can be used to train a general belief tracking model which can operate across all of these domains, exhibiting superior performance to each of the domain-specific models. We propose a training procedure which uses out-of-domain data to initialise belief tracking models for entirely new domains. This procedure leads to improvements in belief tracking performance regardless of the amount of in-domain data available for training the model. ... : Accepted as a short paper in the 53rd Annual Meeting of the Association for Computational Linguistics (ACL 2015) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/1506.07190 https://dx.doi.org/10.48550/arxiv.1506.07190 BASE Hide details 8 Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking ... Wen, Tsung-Hsien; Gasic, Milica; Kim, Dongho. - : arXiv, 2015 BASE Show details

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