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EFFECTS OF THE USER MODEL ON SIMULATION-BASEDLEARNING OF DIALOGUE ...
mi.eng.cam.ac.uk/~sjy/papers/swsy05.pdf20 Feb 2018: The COMMUNICATOR systems in contrast onlyrequest between 24% and 43% of the unknown slots in each state. -
Photo-Realistic Expressive Text to Talking Head Synthesis Vincent…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2013-Interspeech-EVTTS.pdf13 Mar 2018: 6] Cao, Y., Tien, W., Faloutsos, P. and Pighin, F., “Expressivespeech-driven facial animation”, ACM TOG, 24(4):1283–1302,2005. -
An attention based model for off-topic spontaneous spoken response ...
mi.eng.cam.ac.uk/~ar527/malinin_slate2017.pdf15 Jun 2018: Theacoustic models are trained on 108.6 hours of BULATS test data(Gujarati L1 speakers) using the HTK v3.5 toolkit [24, 25].A Kneser-Ney trigram language model is trained ... INTERSPEECH, 2015. [24] S. Young et al., The HTK book (for HTK Version 3.4.1). -
Boosted Manifold Principal Angles for Image Set-Based Recognition…
mi.eng.cam.ac.uk/~cipolla/publications/article/2007-PR-Kim.pdf13 Mar 2018: recognition from face motion manifolds.Image and Vision Computing, 24(5),. 2006. (in press). ... 24] R. O. Duda, P. E. Hart, and D. G. Stork.Pattern Classification. -
Still Talking to Machines (Cognitively Speaking) Steve Young…
mi.eng.cam.ac.uk/~sjy/papers/youn10a.pdf20 Feb 2018: partition ex-plicitly records the fact that x = a and the existing partitionis updated to record the fact that x = ā [24]. -
Efficiently Combining Contour and TextureCues for Object Recognition…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2008-BMVC-Shotton.pdf13 Mar 2018: Puzicha. Shape matching and object recognition using shape contexts. PAMI,24(24):509–522, 2002. ... PAMI, 24(5),2002. [4] P. Dollár, Z. Tu, H. Tao, and S. -
Context adaptive training with factorized decisiontrees for HMM-based …
mi.eng.cam.ac.uk/~sjy/papers/yzmy11.pdf20 Feb 2018: 24].3 Available at http://mi.eng.cam.ac.uk/˜farm2/emphasis.4 Cohen’s Kappa cannot be used here because the phrases are not distinct elements. ... Interspeech, 2010, pp. 410–413. [24] S. Young, G. Evermann, M. Gales, T. -
On-line Active Reward Learning for Policy Optimisationin Spoken…
mi.eng.cam.ac.uk/~sjy/papers/sgmb16.pdf20 Feb 2018: Thomson and Young2010] Blaise Thomson and SteveYoung. 2010. Bayesian update of dialogue state:A pomdp framework for spoken dialogue systems.Computer Speech and Language, 24:562–588. -
Reward Estimation for Dialogue Policy Optimisation Pei-Hao Su, Milica …
mi.eng.cam.ac.uk/~sjy/papers/sugy18.pdf20 Feb 2018: In this section, a Gaussianprocess-based reward estimator is described which uses active learning tolimit intrusive requests for feedback and a noise model to mitigate the effectsof inaccurate feedback [24]. ... 24. Figure 13: The number of times each -
doi:10.1016/j.imavis.2007.01.006
mi.eng.cam.ac.uk/~cipolla/publications/article/2008-IVC-Vogiatzis.pdf13 Mar 2018: Fortu-nately a number of efficient approximate algorithms havebeen proposed such as graph cuts [1] and belief propaga-tion [24]. ... 1194–1201. [24] J. Sun, H,-Y Shum, N.-N. Zheng, Stereo matching using beliefpropagation, in: Proceedings of ECCV, 2002,
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