In this paper, methods of Gaussian Mixture Model (GMM) are presented for both silence/voiced/voiceless segmentation and tone decision in Mandarin continuous speech recognition system. GMM has been used for silence/voiced/voiceless segmentation before, but the feature parameters can be modified to improve both accuracy and speed. As a popular method in pattern recognition, GMM is first proposed ...

We 1 develop some theoreti al results for a robust similarity measure named generalized minmax (GMM). This similarity has dire t appli ations in ma hine learning as a positive de nite kernel and an be e iently omputed via probabilisti hashing. Owing to the dis rete nature, the hashed values an also be used for e ient near neighbor sear h. We prove the theoreti al limit of GMM and the onsisten y...

We propose the “generalized min-max” (GMM) kernel as a measure of data similarity, where data vectors can have both positive and negative entries. GMM is positive definite as there is an associate hashing method named “generalized consistent weighted sampling” (GCWS) which linearizes this (nonlinear) kernel. A natural competitor of GMM is the radial basis function (RBF) kernel, whose correspond...