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A LANGUAGE SPACE REPRESENTATION FOR SPEECH RECOGNITION
mi.eng.cam.ac.uk/~mjfg/icassp15-ragni.pdf18 May 2015: There are many options to select the form of rep-resentation of the clusters and the combination method to employ[18, 17, 13, 24, 25]. ... 20, no. 6, pp. 1713–1724, 2012. [24] V. Diakoloukas and V. -
IEEE SIGNAL PROCESSING MAGAZINE [128] MAY 2010 This article ...
mi.eng.cam.ac.uk/~sjy/papers/youn10.pdf20 Feb 2018: THE HIDDEN INFORMATION STATE SYSTEMA block diagram of the HIS system is shown in Figure 13 [23], [24]. ... The history states record grounding and query status information but the details are not relevant here (see [24]). -
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. -
paper.dvi
mi.eng.cam.ac.uk/~mjfg/segdisc_2012.pdf19 Oct 2012: α̂(r) = argminα. {. F(. α, w(r), O(r); α̂(r1))}. (15). Conditional Maximum Likelihood[24]:. ... . . . . . . . vj V (24). whereV is the vocabulary of segment identities. -
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. -
crosseval_diff-reward2b.ps
mi.eng.cam.ac.uk/~sjy/papers/kgjm10.pdf20 Feb 2018: Yu. 2009. The Hidden InformationState model: a practical framework for POMDPbased spoken dialogue management.ComputerSpeech and Language, 24(2):150–174. -
main.dvi
mi.eng.cam.ac.uk/~sjy/papers/ywss05.pdf20 Feb 2018: At this point, the dialog state probabilities given by equation 24 are omputed. ... P1. find P2. (a) task 1.0. P1 b=1.0. b=0.7. b=0.3. b=0.24. -
Towards Learning Orientated Assessment for Non-native Learner Spoken…
mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/ALTA_Sheffield_20190306.pdf21 Feb 2022: 300 300. 25.5. 400 24.5. 400 24.4. ASR on Non-native Speech (2). • ... Thai dh d 7.24 oh aa 5.21. 30. • Top 2 recurrent substitution errors for speakers in each L1. -
JournalPaperDRAFTV0.20
mi.eng.cam.ac.uk/~sjy/papers/wipy05a.pdf20 Feb 2018: J. D. Williams, P. Poupart, S. Young 24 March 2005. University of Cambridge, Dept. ... 24. not “brittle” – i.e., they do not fail catastrophically as the actual value of errp deviates from that used in training. -
Machine Intelligence Laboratory
mi.eng.cam.ac.uk/Main/GMT_EqnSurfIn the Windows version this will be saved in uncompressed 24-bit.
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