Statistical pattern recognition approach to speech segmentation

A Pattern Recognition Approach to Image Segmentation

The objective of the present paper is to describe a pattern recognition approach for image segmentation. First, in the introduction, we describe the general aspects of uniformity and texture recognition. Then we provide a mean-based feature extraction approach for uniformity analysis and a moment-based one for texture analysis. In the classification stage we propose both supervised and also uns...

Statistical Approach to Clustering in Pattern Recognition

Clustering is a typical method of grouping data points in an unsupervised learning environment. The performance of most clustering algorithms is dependent on the accurate estimate of the cluster number, which is always unknown in the real applications. In this paper, we propose a new parametric approach, which starts with an estimate of the local distribution and efficiently avoids pre-assuming...

Introduction to Statistical Pattern Recognition

Annotation: Pattern recognition problem is briefly characterized as a process of machine learning. Its main stages (dimensionality reduction and classifier design) are stated. Statistical approach is given priority here. Two approaches to dimensionality reduction, namely feature selection (FS) and feature extraction (FE) are specified. Though FS is a special case of FE, they are very different ...

Statistical Pattern Recognition Statistical Pattern Recognition Second Edition

Speech segmentation without speech recognition

In this paper, we presented a semantic speech segmentation approach, in particular sentence segmentation, without speech recognition. In order to get phoneme level information without word recognition information, a novel vowel/consonant/pause (V/C/P) classification is proposed. An adaptive pause detection method is also presented to adapt to various background and environment. Three feature se...