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1 Mar 2000: 24.4. F5. 28.6. 23.8. 27.1. 26.5. FX. 58.5. 55.2. 56.8. 55.0. ... 39.6. 25.1. 37.2. F4. 24.1. 24.7. 24.5. 22.6. F5. 27.6. 25.8.

1 Mar 2000: S. 0.56. 98.24. 1.20. T. 0.00. 1.19. 98.81. a). M. S.

23 Jun 2003: 0 26.1 23.7P3.3-cn 20.4 24.3 26.6 24.0final 19.9 23.5 25.8 23.3. ... 320xRT 2002† 19.8 24.3 27.0 23.910xRT 2002† 22.3 27.7 31.0 27.2 14%.

16 Jun 2000: Of the 110 seconds worth of news'' rejected by the system with shorter windows, 24 seconds was due to an interview with Bill Clinton being re-broadcast, and the rest was

3 Nov 2023: 24] Semi-supervised pre-training and back-translation fine-tuning for translation of formal and informal text.

2 Nov 2000: 1003 250 - 225.85 192.66 224.24 187.371003 250 158.98 151.15 158.68 149.371003 500 - 230.96 193.86 228.93 188.111003 500 159.77

1 Mar 2000: Comparing Table 4 with Table 3 the advantage of including two passes can clearly be seen: on BNeval98 the error rate was reduced by 24% while the overall computation was increased

14 Jun 2004: 9.1. 25.54. 29.7. 46.14. CU. MIT. 2.1. 2.5. 5.3. 24.23. 24.7. ... Adv. Seg. Clust. Score. Metric. NONE. CUED. MIT. 24.23. Primary. CUED_TDT4.

12 May 2003: This paper presents a methodfor hand tracking that estimates the pose of a 3D hand modelconstructed from truncated quadrics by using an UnscentedKalman filter [18, 24]. ... Originally published in1952. [24] E. A. Wan and R. van der Merve.

30 Mar 2000: 24.7. 35.5. 10181. Windowing - 30s@15s. 33.9. 46.1. 18669. Windowing - 30s@10s. ... 55.73. 52.75. 43.89. ----. Sheffield. 32.0. 44.7. 60.66. 52.85. 42.47. 38.24.

RES_VID_GREY_THRESH. long. 24. IMAGE. When recording Doppler data, the intensity threshold (as an 8-bit integer) below which a colour video signal is regarded as being grey-scale.

23 Feb 2002: 183k articles in [24]), in previous work we found that increasing the parallel corpus size to approximately 110k articles did not help performance [16]. ... 45.02. cr-limsi2. 21.2. 37.24. 39.28. 41.62. 44.12. cr-limsi1. 21.5. 36.56. 38.57.

22 Jul 2010: Achievements. Freehand RF 3D ultrasound acquisition. We have successfully developed the real-time, RF 3D ultrasound acquisition system [24]. ... 24] G. Treece, R. Prager and A. Gee. Freely available software for 3D RF ultrasound.

2 Nov 2000: 225.85. 192.66. 224.24. 187.37. 1003. 250. 158.98. 151.15. 158.68. 149.37.

19 Apr 2000: 39.39. 27.42. 752913. -. -. N. B. 95.8. 37.52. 24.92. 698461. -. -. ... In Proc. TREC-7, NIST SP 500-242, pages 1-24, Gaithersburg, MD.

5 Oct 2000: The bigram 1-best hypotheses had a 24.6% word error rate (WER) and a Lattice WER (LWER) of 6.2%...

20 Feb 2018: Trial # users average # calls median # callsAMT 140 6.5 2Cambridge 17 24.4 20. ... vol. 24, no. 2, pp.150–174, 2010. [7] Amazon, “Amazon Mechanical Turk,” 2011.

22 Sep 2005: The experiments reported in this paper use a development set of 24 US broadcast news shows, denoted.

20 Jun 2023: 24/36. Spoken Language Assessment. 25/36. Grader Uncertainty: Ensemble-Based. Within 0.5 CEFR-Level Within 1.0 CEFR-Level26/36.

12 May 2003: Belongie,J. Malik, and J. Puzicha. Shapematchingandobjectrecognitionusingshapecontexts. IEEE Trans.PatternAnalysisand Machine Intell., 24(4):509–522,April 2002.

1 Jan 2024: 1300. Light Bluish Gray Technic, Gear 24 Tooth (New Style. with Single Axle Hole).

7 Oct 2001: The overall word error rate for the data was 24.8%, the lowest in the TREC-7 SDR evaluation, with the baselines provided by NIST offering 33 and 42%. ... The final project publications include the TREC-9 paper [24] , two papers in the International

9 Nov 2023: Talk. [24] Context-dependent alignment models and hierarchical phrase-based translation with weighted finite state trans-ducers, GALE PI Meeting, Tampa, FL, USA, May 2009. ... Association for Computational Linguistics, November 2021. [24] BO-HSIANG TSENG,

20 Feb 2018: error rate of 33.2 %, and for the first and secondorder derivatives the error rates of the classifiers are 33.1 %and 24.2 %, respectively. ... 24.8 42.4par 22.7 13.1 21.7 32.4 32.7 25.2 27.4 45.1.

27 May 2004: purpose WER. P1 supervision for VTLN 34.2P2 supervision for MLLR 28.4P3 lattice generation 24.8. ... System (P4) A B C DSAT HLDA SPron non-HLDA23.0 23.6 23.4 24.8.

13 Jun 2013: 2011, pp. 24–29, Ieee. [13] M. J. F. Gales and F.

23 Jun 2003: Automatic Segmentation. Segmentation Diarisation CER (%)MS FA Tot. Manual 1.2 24.5 25.6 49.8Automatic 3.7 8.3 11.9 50.8.

19 Dec 2006: Uncertainty 1 4 16 256. Clean — 33.2. SPLICENo. 24.6 20.7 17.0 12.3FE-CMLLR 16.3 15.3 12.8 13.5.

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.

10 Jan 2005: show. (b) Mean DER across all 24 development shows whenonly including c0 in clustering if the mean value is above a criticalthreshold. ... RT-04 RT-04 RT-04 23.86 24.12. Table 12. Progress since RT-03s on theeval04f data.

20 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]).

20 Feb 2018: U| 103 and |M| 103. (24). Goals are composed ofNC constraints taken from theset of constraintsC, andNR requests taken from the setof requestsR.

10 Oct 2001: X) 64.95 61.25 46.82 45.24 44.27 30.33 39.98 42.14 38.65 35.72 BE DBRF2 (X) 66.57 65.89 45.21 ... BE DBRF (X) 69.41 69.12 52.55 51.73 51.14 36.86 41.99 44.13 42.14 42.05 BE [PR]BRF (A) 66.24 64.53

6 Nov 2000: Some discriminative training schemes, such as frame-discrimination [14, 24], try to over-generate training set con-fusions to improve generalisation. ... In [24] it was shownthat the improvements obtained by FD were at least as goodas those reported by

29 Nov 2017: Network Interpretation [24]. Standard /ay/ Stimulated /ay/. • Deep learning usually highly distributed - hard to interpret• awkward to adapt/understand/regularise• modify training - add stimulation regularisation• improves ASR performance.

15 Nov 2005: MORTGAGE DEFAULT: CLASSIFICATION TREES ANALYSIS. David Feldman and Shulamith Gross#. March 24, 2003. ... 24. robust Cross-Validation method. Since it does not have any particular.

14 Sep 2006: 24, 18]. Both systems group an image’sspatial features, performing a global annealing optimizationthat propagates the certainty at distinct person-boundaries touncertain areas where those people’s outlines are ambigu-ous. ... 24] P. Tu and J.

11 Oct 2023: Audio Speech Lang.Process., vol. 24, no. 8, pp. 1438–1449, 2016. 9. ... Signal Processing,ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pp.

7 Oct 2001: 8;,=&"vZ$9V K)i!Zi9V ;)Î$9h ;& ;=!"p;) / -,H;&AP,!#P6 %S+[#( 24 )g(>@{7cPU(.( 7;'8;(! ... 9V @24 Ì ' $;S+[ -c.,=",=&8U - PU -"P7,=!)G,=&,=&,H&8g- / -( -,=,Hg",=-;' - -r( -,!K9$(-v> zXx}24 & -)g=![] Ç4',!

20 Feb 2018: Per-turn. WER. Per-dialog WER. None 2 6 24 83 % 0 % 0 % Low 4 12 48 83 % 32 % 28 % Med 4 12 48 77 % 46 % 41 % Hi 2 6 24 ... Dataset. Metrics (task & user sat). R2 Significant predictors. ALL User-S 52 % 1.03 Task ALL User-C 60 % 5.29 Task – 1.54

20 Feb 2018: Computer Speech and Language,24(4):562–588. O Tsimhoni, D Smith, and P Green. ... Computer Speech andLanguage, 24(2):150–174.

20 Feb 2018: wwpos 24.52 11.29 18.47wspos 11.33 4.91 3.31wpof s 1.13 4.82 8.82wppof s 24.27 6.49 10.54wonset 15.08 0.33 ... 47.3% 52.7%. 75.3% 24.7%. Figure 3: Categorical quality ratings for spectral conversion duration conversion HMM-based contour generation.

20 Feb 2018: POMDP-based Hidden Information State (HIS) DialogueSystem [22, 24]. ... of ICASSP, Honolulu, HI, 2007. [24] B. Thomson, J. Schatzmann, K.

20 Feb 2018: 3.3. The agenda-based simulated user. The agenda-based user simulator [24, 25] factorises the user stateinto an agenda and a goal. ... 23] TopTable, “TopTable,” 2012, https://www.toptable.com. [24] J Schatzmann, Statistical User and Error Modelling

20 Feb 2018: 24, no. 2, pp. 395–429, Apr. 2010. [8] Pierre Lison, “Multi-policy dialogue management,” inProceedings of the SIGDIAL 2011 Conference, Strouds-burg, PA, USA, 2011, SIGDIAL ’11, pp. ... 24, no. 4,pp. 562–588, 2010. [18] T Jebara, R Kondor, and A

20 Feb 2018: 1.2% 2.0%Request 17.4% 24.5% 18.4% 24.4%. ... 24, no. 4, pp. 562–588, 2010. [22] J Peters and S Schaal, “Natural Actor-Critic,” Neurocomput-ing, vol.

20 Feb 2018: In control tests by humanusers, the success rate of the system was 24.5% higher thanthe baseline Lets Go! ... Com-pared to the BASELINE system, the BUDSLETSGO systemimproves the dialogue success rate by 24.5% and the worderror rate by 9.7%.

20 Feb 2018: The static feature set comprised 24 Mel-Cepstral coefficients,logarithm of F0 and aperiodic energy components in five frequency. ... 12 sentences werethen randomly selected to make up a testset for each listener, leadingto 24 wave files pairs (12 for

20 Feb 2018: Corpus Mean (SD) Grades Correlationn Human Auto R p. L 21 24.2 (3.1) 17.1 (1.9). ... 69C 50 24.0 (3.0) 15.6 (3.3). 59. 01. Table 2: Mean (standard deviation) of human andautomated grades, along with Pearson’s correla-tions between the human and

20 Feb 2018: 0.24. 0.22. 0.20. 0.18. 0.16. Log-. likel. ihoo. dpe. rmic. ro-tu. ... 24, no. 4, pp. 562–588, 2010. [14] SpaceBook. EC FP7/2011-16, grant number 270019.