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16 Feb 2008: "$#&%'(),.-%/01 " 2-3 2 42 56879;:<=1) >?1 01@ " ABC". DE F(GH42IJKC7 #%L88NM :O88 F1@ ". PQSRUTWVYXUT&ZX[1]_VYXCaVYT.

17 Sep 2008: Uncertainty Decoding forNoise Robust Speech Recognition. Hank Liao. Sidney Sussex CollegeUniversity of Cambridge. September 2007. This dissertation is submitted for the degree ofDoctor of Philosophy to the University of Cambridge. Declaration. This

11 Jan 2008: γm(t)ot. )(24). γm(t) is the component posterior derived from P (θ|O, H, λ̂k1).For the frame independent assumption it is necessary to obtain. ... where G and k are the standard sufficient statistics given in equa-tions 23 and 24, except that γm(t)

16 Feb 2008: 233.3.3 Obtaining Confusions from a Lattice. 24. 3.4 Obtaining Relevant Training data for the Binary Classifiers.

5 Sep 2008: µPRA = pW TWS TSI TspI′. (24). This is a measurement of system accuracy, and includes errors from every component of thesystem.

16 Feb 2008: 232.8.4 Phrase Extraction from a Lattice. 24. 2.9 ASR Lattice Pruning for Translation. ... or word lattices [24, 25]. N-Best translation is straightforward: a text-based SMT.

15 Aug 2008: Cambridge UniversityEngineering Department. August 2008 24. Instantaneous and Discriminative Adaptation for Automatic Speech Recognition. ... Adaptation Supervision1-Best Lattice Reference. — 29.2 — —. MLLR 27.0 26.7 24.3MLLRDMT 26.2 25.9 23.4.

19 Mar 2008: Foundations and Trends R inSignal ProcessingVol. 1, No. 3 (2007) 195–304c 2008 M. Gales and S. YoungDOI: 10.1561/2000000004. The Application of Hidden Markov Modelsin Speech Recognition. Mark Gales1 and Steve Young2. 1 Cambridge University

6 Mar 2008: The. 6. 20 40 60 80 100sample number. ry=24 a. ry=44 a. ... a). 20 40 60 80 100sample number. ry=24 a. ry=44 a.

13 Jun 2008: Cambridge UniversityEngineering Department. King’s College London Seminar 24. Model-Based Approaches to Robust Speech Recognition. ... p(Y; λ(1)). )λ(2) log. (p(Y; λ(2)). ). . – Related to the Fisher kernel [24].