Speech Recognition of Assamese Numerals Using Combinations of LPC - Features and Heterogenous ANNs

Abstract

A fully automated and effective method of detection of Assamese numerals captured under varied recording conditions and moods is presented here. The work also deals with gender variations taken as part of the speech recognition using a combination of Linear Predictive Code (LPC) and Vector Quantization applied to a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) based system. The SOM and MLPs are used to constitute a Learning Vector Quantization (LVQ) block which is necessitated by the fact that the LPC-VQ methods fail to produce the expected outcome while dealing with numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The performance of the LPC feature set is further compared with that obtained PCA features applied to the same LVQ block. © Springer-Verlag Berlin Heidelberg 2010.