P. Beyerlein, M. Ullrich: Hamming Distance Approximation for a Fast Log-Likelihood Computation for Mixture Densities. Proc. Europ. Conf. on Speech Communication and Technology, Madrid, Spain, pp. 1083-1086, September 1995.  Home/Search   Document Not in Database   Summary   Related Articles

....effort can be achieved by integrating the projection search technique into other fast loglikelihood computation methods. To this purpose, we combine the projection search technique with two wellknown fast log likelihood computation methods, namely the Hamming distance approximation (HDA) [2] and a vector quantization (VQ) method for mixture density preselection [4, 8] The organization of this paper is as follows. In Section 2, we briefly describe the task of log likelihood calculations using Laplacian mixture densities. In Section 3, we review the fast log likelihood computation ....

.... Due to the simplicity of the projection search algorithm and for further speeding up the log likelihood calculations, we have combined the projection search with the following well known fast log likelihood techniques: ffl preselection (VQ) method [4] ffl Hamming distance approximation (HDA) [2]. The idea of these so called hybrid fast log likelihood techniques can be viewed as a two step selection process. x x y y z z e 1 X 2 X 2 Y 1 Y X Y Z 2 e H H H H H X X X X X X e e e e e Figure 2. Illustration of the slicing process using the projection search ....

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P. Beyerlein, M. Ullrich: Hamming Distance Approximation for a Fast Log-Likelihood Computation for Mixture Densities. Proc. Europ. Conf. on Speech Communication and Technology, Madrid, Spain, pp. 1083-1086, September 1995.

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