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  2. 20 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
  3. AUTOMATIC COMPLEXITY CONTROL FOR HLDA SYSTEMS X. Liu, M. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/liu_icassp2003.pdf
    19 Sep 2003: Fig. 1. Test set word error rate for all possible models, with thestandard front-end 12, 16 and 24 component performance. ... The best perfor-mance, 36.8%, was obtained using 24 components per state and anHLDA projection from 52 dimensions to 38
  4. 20 Feb 2018: partition ex-plicitly records the fact that x = a and the existing partitionis updated to record the fact that x = ā [24].
  5. Applying Deep Learning in Non-native Spoken English Assessment

    mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/APSIPA2019_Knill.pdf
    21 Feb 2022: 1.0 indicates within one CEFR grade-level. 24/45. Assessment System Performance. • ... 1.0 indicates within one CEFR grade-level. 24/45. Performance Analysis. 25/45.
  6. DEVELOPMENT OF THE 2003 CU-HTK CONVERSATIONAL TELEPHONE…

    mi.eng.cam.ac.uk/reports/svr-ftp/evermann_icassp2004.pdf
    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.
  7. A HYBRID DISPLACEMENTESTIMATION METHOD FOR ULTRASONIC ELASTICITY…

    mi.eng.cam.ac.uk/reports/svr-ftp/chen_tr615.pdf
    13 Nov 2008: IEEE Transactions on MedicalImaging, 23:153–163, 2004. [24] A. Pesavento, C. Perrey, M. ... Ultrasound in Medicine and Biology, 24:427–441, 1998. [31] R. Zahiri-Azar and S.
  8. PROC IEEE, VOL. 101, NO. 5, 1160-1179, 2013 1 ...

    mi.eng.cam.ac.uk/~sjy/papers/ygtw13.pdf
    20 Feb 2018: A similar approach is takenin [24], except that both slot values and their complements areused to build a frame. ... R(θ) = 1N. Nn=1. Tn1t=0. θ log π(ânt |bnt ,θ)Q(bnt , ânt ) (24).
  9. Towards Learning Orientated Assessment for Non-native Learner Spoken…

    mi.eng.cam.ac.uk/~kmk/presentations/ALTA_Sheffield_20190306.pdf
    8 Mar 2019: 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.
  10. paper.dvi

    mi.eng.cam.ac.uk/~mjfg/segdisc_2012.pdf
    19 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.
  11. A LANGUAGE SPACE REPRESENTATION FOR SPEECH RECOGNITION

    mi.eng.cam.ac.uk/~mjfg/icassp15-ragni.pdf
    18 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.

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