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5 Jul 2022: previoustokens. To achieve more accurate estimation, sequence-to-sequence models are usuallyautoregressive [24]. For autoregressive models, a standard approach is teacher forcing, which guides a modelwith reference output history during training.

29 Apr 2006: average 92.0 64.1 58.3 17.0std 7.8 9.2 24.3 8.8. video sequences of the person in arbitrary motion (signif-icant translation, yaw and pitch, ... cluded and expression variant faces from a single sample per class.PAMI, 24(6), 2002.

25 May 2004: Adaptation hypothesis true transCN (27.0). MLLR 27.7 27.0 26.1MMI-DLT 27.5 26.8 24.8MPE-DLT 27.3 26.9 23.2.

26 Sep 2016: This serves the basis ofstructured discriminative models including SSVMs. Classifica-tion is performed by solving a semi-Markov inference problem[24]:. ... 994–1006, 2010. [24] S. Sarawagi and W. W. Cohen, “Semi-Markov conditional randomfields for

10 Feb 2012: The like-lihood is then computed as. p(yyyt |m). p(xxx|yyyt )p(xxx|m)dxxx (24). ... Though intuitively well motivated, from (24) it can be seen that the likelihood is notmathematically consistent.

12 Apr 2005: SATSPAMcmllr+ 25.0 17.6 21.4 17.6cmllr 24.9 17.5 21.3 17.5. Table 2.

3 Feb 2015: This isa very clean model, with no significant correlations between the covariates, the largest correlation coefficientbeing 0.24 between age and one of the site labels.

22 Mar 2017: FLP Web FLP Web (#) ASR KWSSwahili 294 – 24.4 0 8.2 8.5 19.6Dholuo 467 1,217 17.5 18.8 6.1 3.0 10.0Amharic 388 ... 4, pp. 1738–1752, 1990. [24] P. Ghahremani, B. BabaAli, D. Povey, K.

10 Nov 2015: 24 Engineering Part IIB: Module 4F10 Statistical Pattern Processing. Cost of Mis-Classification.

21 Nov 2023: 23. 3.4 Summary. 24. 4 Results and Discussions 254.1 In-context Learning for NMT. ... The loss function can be any string-to-string distance function, or the negative of string-to-string alignment function such as BLEU [24] and BLEURT [34] (see Section

8 Mar 2000: 36.5F4 24.2 25.1 23.1 21.3F5 25.7 24.1 25.9 23.0FX 57.2 53.7 57.1 50.4. ... 24.1 29.9ROVER BN2/3/gd ic 1/4 15.8 9.4 15.2 19.5 26.9 19.4 22.1 29.1.

10 May 2000: ID BASE BRF UBRF3k 22.2 24.4 33.37k 33.8 37.5 44.3. 14k 41.4 47.6 51.827k 43.0 49.7 53.855k 43.5

16 Sep 2003: CambridgeUniversityEngineeringDepartment. EARSMeetingSept20037. X.Liu&M.J.F.Gales:AutomaticModelComplexityControlUsingMarginalizedDiscriminativeGrowthFunctions. IssueswithMLparadigm.

26 Jan 2015: 2.33†† (1.70, 3.21) 2.44†† (1.61, 3.71) 2.24†† (1.51, 3.31). ... Journal of Bone and Mineral Research 24 (3), 468–474. Johnell, O., Kanis, J.

19 Sep 2006: Cambridge University Press, 1999. [FB81] FISCHLER M., BOLLES R.: Random sample consensus:A paradigm for model-fitting with applications to image analysisand automated cartography.CACM 24, 6 (1981), 381–395.

25 Feb 2019: It calculates the denominator by directly applying forward-backward computations [23, 24] on an unpruned denominator graphon GPU hardware. ... In Proc. ICASSP, volume 2,pages 605–608, 1996. [24] P. C. Woodland and D.

18 Feb 2009: 24). where γ(m)o,t is the posterior probability of component m given the observation sequence O, bias. ... parameter Mb, and model set M. Differentiating equation 24 with respect to µ̂(rm)b and Σ̂(rm).

17 Jan 2008: Among several techniques for displacement estimation [12, 24], correlation maximization wasthe first to be proposed and remains the most widely used [16]. ... As p1 is the only point ready for processing,it is selected and fed into any suitable

31 Aug 2019: Thesefeatures may include various statistics extracted from audio, acousticmodels, language models and lattices [24]. ... 24] T. Schaaf and T. Kemp, “Confidence measures for spontaneousspeech recognition,” in ICASSP, 1997.

5 Sep 2008: H. Berman. Engineering a freehand 3D ultrasoundsystem. Pattern Recognition Letters, 24:757–777, 2003. ... Ultrasound in Medicine & Biology, 24(6):855–869, 1998. F. Rousseau, P. Hellier, and C.

19 Apr 2000: Of the 110 seconds worth of “news” rejected by the sys-tem with shorter windows, 24 seconds was due to an inter-view with Bill Clinton being re-broadcast, and the

21 Nov 2006: b. . . . . (24). One candidate for estimating the decision bound-ary is the Support Vector Machine (SVM).

19 Feb 2007: H. Berman. Engineering a freehand 3D ultrasoundsystem. Pattern Recognition Letters, 24:757–777, 2003. ... Ultrasound in Medicine & Biology, 24(6):855–869, 1998. R. W. Prager, A.

19 May 2003: 3.4 100 (6.5, 4.6, -15.3) 3.4 100 (7.7, 2.1, -15.3) 4.0arm 30 100 (24.3, -5.1, -9.3) 5.1 100 ... With the full search range,the low resolution search finds a false minimum absolute difference at offset (8, 48, 24) pixels(in dividing plane coordinates).

17 Oct 2000: 704/c 26.3 15.570a/b 10.3 1.970f/d 18.8 7.670w/c 24.2 15.8. Table 1: Lattice error rates for several development test speakerswith ... a fg 14.24 —HMM-2 thresh. b fg 13.81 —HMM-2 thresh. c fg 13.71 6.68.

5 Dec 2003: CACM, 24(6):381–395, June 1981. [6] C. Harris and M. Stephens. A combined corner and edge detector.

25 Mar 2004: This system gave a diarisation error of 24.46% on the develop-ment and 23.85% on the evaluation data. ... Adv Seg Clust Score MetricNONE CUED MIT 24.23 PrimaryCUED TDT4 MIT MIT 28.26 Secondary.

15 Feb 2005: 0.16 0.18 0.2 0.22 0.24 0.2612. 14. 16. 18. 20. 22. ... Cambridge UniversityEngineering Department. RT04 EARS workshop 24. Recent Developments at Cambridge in Broadcast News Transcription.

16 Mar 2005: H. Berman. Engineering a freehand 3Dultrasound system. Pattern Recognition Letters, 24(4–5):757–777, 2003. ... Ultrasoundin Medicine and Biology, 24(9):1243–1270, 1998. [22] R. W. Prager, A.

20 Feb 2018: Effective Handling of Dialogue State in the Hidden. Information State POMDP-based Dialogue Manager. MILICA GAŠIĆ and STEVE YOUNG. Cambridge University Engineering Department. Effective dialogue management is critically dependent on the

31 Aug 2019: may include embeddings [24], acoustic andlanguage model scores and other information. ... 24] T. Mikolov, I. Sutskever, K. Chen, S. S. Corrado, and J.

29 May 2012: All transitions in this language. 15. 4. classifiers. ml mpeDiscriminative training L2 std dev subset all dataFixed scaling factor 30.5 24.4Scaling factor 53.5. ... Full language model. 2.0 1006 24.88.5 1006 24.41.2 1005 24.42.7 1005 24.54.4 1005 30.8.

26 Sep 2016: IEEE, 2011, pp.24–29. [9] R. Gemello, F. Mana, S. Scanzio, P.

5 Oct 2007: Ultrasonic Imaging, 24(1):1–12, January 2002. [14] L. Mercier, T. Langø, F. ... Ultrasound inMedicine and Biology, 24(9):1243–1270, December 1998. [18] M. O’Donnell and S.

26 Mar 2005: 12.5. 13. 13.5. 14. 14.5. 15. SID Threshold. Dev. (24. sh. ... 11. 11.5. 12. 12.5. 13. SID Threshold. Eva. l (24. sh.

10 Aug 1999: 35 and P02 =. 24. a11 a12 a14 a13a21 a22 a24 a230 0 0 a33. ... F =. 24. 0 0 a24a330 0 a14a33. a24a11 a14a21 a24a12 a14a22 a24a13 a14a23.

25 May 2004: System MPE Prior eval03 Male Female. MPE-GI Dynamic MMI 25.9 27.3 24.5MPE-GD MPE-GI model 25.6 27.1 24.1. ... Gaussianised 29.8 21.9 26.0CN 28.7 21.3 25.1. CNC 28.1 20.8 24.6. •

16 Sep 2005: Pattern Recognition Letters, 24:757–777, 2003. [8] A. H. Gee, N. E. ... Ultrasound in Medicine & Biology, 24(6):855–869, 1998. [18] F. Rousseau, P.

9 Oct 2015: Telugu. VLLP 0.838 57.0Blogs 0.128 2625.6News 0.000 893.0Subtitles 0.024 24.9TED 0.000 18.8. ... 24] Z. Tüske, J. Pinto, D. Willett, and R. Schlüter, “Investigation oncross- and multilingual MLP features under matched and mis-matched acoustical

20 Aug 2009: There also exists some studies that considerthe above mentioned similarity measures for multimodality fusion of US images with MRI [4, 17,21] and CT [22, 24, 25]. ... M. Treece, and L. Berman. Engineering a freehand 3D ultrasoundsystem. Pattern

19 Jun 2023: conversational assessment. 24. Applying Foundation Models to Auto-marking: Neural Text Grader.

20 Feb 2018: Stochastic Language Generation in Dialogueusing Factored Language Models. François Mairesse University of Cambridge. Steve Young University of Cambridge. Most previous work on trainable language generation has focused on two paradigms: (a)using a

29 Apr 2004: 29.44 0 6standard-BIC-judge, full cov 24.62 2 2standard-BIC-judge, diag cov 23.90 3 1standard-BIC-judge, 128mix GMM 23.76 5 1IDIAP-BIC-judge, full ... 37.92 10.74 24.62BIC-judge, diag cov 30.30 19.94 18.11 31.05 37.92 10.74 23.90BIC-judge, 128mix GMM

22 Mar 2004: BIC-global (2-way) 6.25 6.25 26.13 25.21BIC-local (2-way) 7.25 - 25.54 25.12BIC-local (2-way) - 6.75 26.47 24.27. • ... Approx. 8% absolute (24% relative) reduction in DER. • Stability also greatly increased: standard deviation when using many input

8 Mar 2000: M S T. M 82.11 17.89 0.00N 15.27 84.22 0.51S 0.56 98.24 1.20T 0.00 1.19 98.81.

15 Jun 2017: How Does the Femoral Cortex Depend onBone Shape? A Methodology for the Joint. Analysis of Surface Texture and Shape. A. H. Gee, G. M. Treece and K. E. S. Poole. CUED/F-INFENG/TR 70415 June 2017. Cambridge University Engineering DepartmentTrumpington

9 Oct 2015: Acoustic likelihood combination and lat-tice combination have been compared in [24]. ... Speech and Audio Processing, vol. 2, no. 1,pp. 217–223, 1994. [24] P.

22 Mar 2017: These weretrained on FLP data of 24 Babel languages and CTS data of 4 addi-tional languages, English, Spanish, Arabic and Mandarin, releasedby LDC. ... Stacked Hybrids were trained withand without stimulated training using monophone initialisation

12 Sep 2018: 23] L. Breiman. Bagging predictors. Machine learning,24(2):123–140, 1996. [24] O. Siohan, B. ... IEEE/ACM Transactions on Audio, Speech,and Language Processing, 24(8):1438–1449, 2016. Introduction. Graphemic English systems.

18 Dec 2003: Results were obtained by re-scoring of 4-gramlattices. Feature Transform Swbd1 Swbd2 Cellular Total— 24.2 40.8 40.4 35.1. ... The resulting 4-gram LM is further interpolated with a class-based trigram languagemodel where the classes are automatically