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22 Mar 2017: Mongolian FLP 511K 24.0K - 4.19 12.19WEB 139M 199.8K 0.93 2.10 5.62. ... 24,no. 11, pp. 2146–2157, 2016. [15] Xie Chen, Yongqiang Wang, Xunying Liu, Mark Gales, andP.

5 Jun 2002: 16 20 24 2833. 33.5. 34. 34.5. 35. 35.5. 36. 36.5. ... Cambridge UniversityEngineering Department. Rich Transcription Workshop 2002 24. Woodland, Evermann, Gales, Hain, Liu, Moore, Povey & Wang: CU-HTK April 2002 Switchboard system.

5 May 2023: zzzt = σsigmoid(WWW zf xxxt WWWzrhhht1 bbb. z) (2.24). rrrt = σsigmoid(WWW rf xxxt WWWrrhhht1 bbb.

23 May 2016: The input features are 24-dimensionallog Mel magnitude spectrum filter banks, pitch, probability of voic-ing, and their derivatives. ... 24, no. 3, pp. 433–444, 2010. [36] Nobuyasu Itoh, Tara N Sainath, Dan Ning Jiang, Jie Zhou, andBhuvana Ramabhadran,

20 Feb 2018: Computer Speech and Language,24(4):562–588. B Thomson, M Gašić, M Henderson, P Tsiakoulis, andS Young. ... Computer Speech and Language, 24(2):150–174. B Zhang, Q Cai, J Mao, E Chang, and B Guo.2001.

20 Feb 2018: S. Young et al. / Computer Speech and Language 24 (2010) 150–174 151. ... 152 S. Young et al. / Computer Speech and Language 24 (2010) 150–174.

13 Jun 2013: with 24% speaking the Central Guangdong, 20%the Northern Pearl River Delta, 19% the Southern Pearl River Delta,19% the Guangxi and Western Guangdong, and 18% the NorthernGuangdong dialects. ... System combination is performed using an

28 Apr 2014: Instead, previous research has beenfocused on using N-best list rescoring for RNNLM performanceevaluation [13, 14, 26, 27, 24]. ... 21, no. 3, pp. 492–518,2007. [24] Y. Si, Q. Zhang, T.

20 Feb 2018: This mixed excitation model hasbeen shown to give significant improvements in the quality ofthe synthesized speech [24]. ... 63.5% 36.5%Male. CF-HMM. 75.5% 24.5%. 0% 25% 50% 75% 100%. Female.

20 Feb 2018: To obtain a closed formsolution of (24), the policy π must be differentiable with respect to θ. ... 10. To lower the variance of the estimate of the gradient, a constant baseline, B, can beintroduced into (24) without introducing any bias [22].

11 Mar 2011: 24, pp. 648–662, 2010. [4] I. Tsochantaridis, T. Joachims, T. Hofmann, and Y.

3 Jul 2018: shows that the CEDM learns to address a relationin up to 24.5% of all dialogues for r = 1.0. ... Computer Speech & Lan-guage, 24(2):150–174. Steve J. Young, Milica Gašić, Blaise Thomson, and Ja-son D.

20 Feb 2018: An advantage of this sparsification approach is that itenables non-positive definite kernel functions to be used in theapproximation, for example see [24]. ... It has already beenshown that active learning has the potential to lead to fasterlearning [24]

20 Feb 2018: 564 B. Thomson, S. Young / Computer Speech and Language 24 (2010) 562–588. ... B. Thomson, S. Young / Computer Speech and Language 24 (2010) 562–588 565.

20 Feb 2018: Com-puter Speech & Language, 24(4):562–588, 2010. Y. Tokuda, T. Yoshimura, T. ... Computer Speech and Language,24(2):150–174, 2010.

20 Feb 2018: Yu. 2009. The Hidden InformationState model: a practical framework for POMDPbased spoken dialogue management.ComputerSpeech and Language, 24(2):150–174.

20 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.

20 Feb 2018: 24, no. 4, Oct. 2010. [16] S. J. Young, G. Evermann, M.

12 Apr 2005: 302k 9k+ 16.0 13.9 24.8 –MLE 415k 9k+ 16.0 13.5 24.3 –. 398k 12k+ 16.1 13.6 24.5 –. 302k 9k+ 13.2 11.2 ... dev04 eval03 dev04f. MLEMPron 16.0 13.6 24.5SPron 15.6 13.5 24.2. MPEMPron 12.9 11.1 19.1SPron 12.7 10.8 18.8.

12 Jul 2016: MPE— 7.15 11.06 14.37 24.54 16.79CML 6.95 11.00 14.29 24.39 16.68large-margin 7.02 10.92 14.16 24.28 ... Therefore the systems use graphemic lex-ica generated using an approach which is applicable to all Unicodecharacters [24].