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Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ...
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Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules ...
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Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ...
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Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules ...
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Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints
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Mrkšić, Nikola; Vulić, Ivan; Ó Séaghdha, Diarmuid. - : Association for Computational Linguistics, 2017. : https://www.transacl.org/ojs/index.php/tacl/article/view/1171, 2017. : Transactions of the Association for Computational Linguistics (TACL), 2017
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Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules
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Vulic, Ivan; Mrkšic, N; Reichart, R. - : Association for Computational Linguistics, 2017. : ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers), 2017
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Neural Belief Tracker: Data-Driven Dialogue State Tracking ...
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Abstract:
One of the core components of modern spoken dialogue systems is the belief tracker, which estimates the user's goal at every step of the dialogue. However, most current approaches have difficulty scaling to larger, more complex dialogue domains. This is due to their dependency on either: a) Spoken Language Understanding models that require large amounts of annotated training data; or b) hand-crafted lexicons for capturing some of the linguistic variation in users' language. We propose a novel Neural Belief Tracking (NBT) framework which overcomes these problems by building on recent advances in representation learning. NBT models reason over pre-trained word vectors, learning to compose them into distributed representations of user utterances and dialogue context. Our evaluation on two datasets shows that this approach surpasses past limitations, matching the performance of state-of-the-art models which rely on hand-crafted semantic lexicons and outperforming them when such lexicons are not provided. ... : Accepted as a long paper for the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017) ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://arxiv.org/abs/1606.03777 https://dx.doi.org/10.48550/arxiv.1606.03777
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Research data supporting "On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems"
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Multi-domain neural network language generation for spoken dialogue systems
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Wen, TH; Gašić, M; Mrkšić, N. - : Association for Computational Linguistics, 2016. : 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Proceedings of the Conference, 2016
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Multi-domain Dialog State Tracking using Recurrent Neural Networks ...
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Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking ...
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Context adaptive training with factorized decision trees for HMM-based statistical parametric speech synthesis
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In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.archives-ouvertes.fr/hal-00746106 ; Speech Communication, Elsevier : North-Holland, 2011, ⟨10.1016/j.specom.2011.03.003⟩ (2011)
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