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5 Jun 2006: 233.2.4 State-Based Speech Enhancement. 24. 3.3 Model-Based Techniques. 243.3.1 Linear Regression Adaptation. ... Ljm(τ ) = p(qjm(τ )|YT , M) (2.24)=. 1L(YT |M) Uj (τ )cjmbjm(y(τ ))βj (τ ). where. Uj (τ ) =. . a1j , if τ = 1N1i=2.

22 Nov 2006: The set of parameters,Θ(sm),. 1Using this form of auxiliary function yields the same update formulae asusing the extended Baum-Welch (EBW) algorithm [24], [25]. ... Wmpem =B2D. 2m B1Dm B0β. (c)m Dm. (23). where. B2 = Σ̂m (24).

22 Nov 2006: ãtj = max{atj , amin} (24). whereãtj is the floored scale factor andamin is the scale floor.In this paper,amin of 0.1 was used.

22 Nov 2006: Factor analysed hidden Markov models for. speech recognition. A-V.I. Rosti , M.J.F. Gales. Cambridge University Engineering Department, Trumpington Street, Cambridge,. CB2 1PZ, UK. Abstract. Recently various techniques to improve the correlation

5 Jul 2006: Complementary System Selection (“Random”). • Variability to systems can be obtained by varying for example:– segmentation and clustering [3]– acoustic model decision tree [24]– acoustic model context (tri/quin-phone) [4]– ... Cambridge

22 Nov 2006: ComponentsGMM A-GMM. EER(%) minDCF EER(%) minDCF. 128 12.17 0.5014 8.62 0.3714256 11.24 0.4704 7.88 0.3467512 11.13 0.4638 7.48

22 Nov 2006: This sensitivity to outliers is a well known feature of the MMI criterion [24]. ... j))}. (24). Each Gaussian component is assumed to be independent of all others.

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.

22 Nov 2006: Km(Oi, Oj ; λ(1)) (24)where Kl(Oi, Oj ; λ) is the dot-product of the log-likelihoodratios and Kc(Oi, Oj ; λ(1)), Km(Oi, Oj ; λ(1)), etc., ... than in the ML case. This is because the MMI base-line performs much better than the ML baseline

22 Nov 2006: HMM ML – 29.4 27.3C-Aug ML CML 24.2 –. HMM MMI – 25.3 24.8C-Aug MMI CML 23.4 –. Table 2. Classification error on the TIMIT core test ... A point of particular interest is that despite poorer statesegmentation—the sufficient statistics fix the