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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 Page: 1 2 Hits 1 – 20 of 33 1 Neighborhood Matching Network for Entity Alignment Wu, Y; Liu, X; Feng, Y. - : The Association for Computational Linguistics, 2020 BASE Show details 2 Understanding (Mis)Behavior on the EOSIO Blockchain Huang, Y; Wang, H; Wu, L. - 2020 BASE Show details 3 Hemipustulopora tuoyuan Liu & Liu & Zágoršek 2019, n. sp. ... Liu, H.; Liu, X.; Zágoršek, K.. - : Zenodo, 2019 BASE Show details 4 Hemipustulopora tuoyuan Liu & Liu & Zágoršek 2019, n. sp. ... Liu, H.; Liu, X.; Zágoršek, K.. - : Zenodo, 2019 BASE Show details 5 Exploiting future word contexts in neural network language models for speech recognition Chen, X.; Liu, X.; Wang, Y.. - : Institute of Electrical and Electronics Engineers (IEEE), 2019 BASE Show details 6 Jointly Learning Entity and Relation Representations for Entity Alignment Wu, Y; Liu, X; Feng, Y. - : Association for Computational Linguistics, 2019 BASE Show details 7 Ensuring interpreting quality in legal and courtroom settings: Australian Language Service Providers’ perspectives on their role Liu, X; Stern, L. - : Roehampton University, 2019 BASE Show details 8 See you in court: How do Australian institutions train legal interpreters? Stern, L; Liu, X. - : Taylor & Francis (Routledge), 2019 BASE Show details 9 Future word contexts in neural network language models Chen, X.; Liu, X.; Ragni, A.. - : IEEE, 2018 BASE Show details 10 ATTITUDES TOWARD HOSPICE CARE: A COMPARISON OF CANTONESE- AND MANDARIN-SPEAKING CHINESE AMERICAN OLDER ADULTS Liu, X; Berkman, C. - : Oxford University Press, 2018 BASE Show details 11 Achieving accuracy in a bilingual courtroom: the effectiveness of specialised legal interpreter training Hale, SB; Liu, X. - : Taylor & Francis (Routledge), 2018 BASE Show details 12 Future word contexts in neural network language models Chen, X.; Liu, X.; Ragni, A.. - : IEEE, 2017 BASE Show details 13 Investigating bidirectional recurrent neural network language models for speech recognition Chen, X.; Ragni, A.; Liu, X.. - : International Speech Communication Association (ISCA), 2017 BASE Show details 14 Investigation of Back-off Based Interpolation Between Recurrent Neural Network and N-gram Language Models (Author's Manuscript) Chen, X; Liu,X; Gales,M J F. - 2016 BASE Show details 15 Sentiment analysis: text, pre-processing, reader views and cross domains Haddi, Emma. - : Brunel University London, 2015 BASE Show details 16 Facial landmark localization by curvature maps and profile analysis Lippold, C. (Carsten); Liu, X. (Xiang); Wangdo, K. (Kim). - 2015 BASE Show details 17 Paraphrastic recurrent neural network language models Liu, X; Chen, X; Gales, Mark; Woodland, Philip. - : IEEE, 2015. : ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2015 Abstract: Recurrent neural network language models (RNNLM) have become an increasingly popular choice for state-of-the-art speech recognition systems. Linguistic factors influencing the realization of surface word sequences, for example, expressive richness, are only implicitly learned by RNNLMs. Observed sentences and their associated alternative paraphrases representing the same meaning are not explicitly related during training. In order to improve context coverage and generalization, paraphrastic RNNLMs are investigated in this paper. Multiple paraphrase variants were automatically generated and used in paraphrastic RNNLM training. Using a paraphrastic multi-level RNNLM modelling both word and phrase sequences, significant error rate reductions of 0.6% absolute and perplexity reduction of 10% relative were obtained over the baseline RNNLM on a large vocabulary conversational telephone speech recognition system trained on 2000 hours of audio and 545 million words of texts. The overall improvement over the baseline n-gram LM was increased from 8.4% to 11.6% relative. ; The research leading to these results was supported by EPSRC grant EP/I031022/1 (Natural Speech Technology) and DARPA under the Broad Operational Language Translation (BOLT) and RATS programs. The paper does not necessarily reflect the position or the policy of US Government and no official endorsement should be inferred. Xie Chen is supported by Toshiba Research Europe Ltd, Cambridge Research Lab. ; This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ICASSP.2015.7179004 Keyword: language model; paraphrase; recurrent neural network; speech recognition URL: https://www.repository.cam.ac.uk/handle/1810/247441 BASE Hide details 18 Paraphrastic language models Liu, X.; Gales, M.J.F.; Woodland, P.C. In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 28 (2014) 6, 1298-1316 OLC Linguistik Show details 19 Use of contexts in language model interpolation and adaptation Liu, X.; Gales, M.J.F.; Woodland, P.C. In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 27 (2013) 1, 301-321 OLC Linguistik Show details 20 Language model cross adaptation for LVCSR system combination Liu, X.; Gales, M.J.F.; Woodland, P.C. In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 27 (2013) 4, 928-942 OLC Linguistik Show details Page: 1 2

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