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Past research in mathematics, acoustics, and speech technology have provided many methods for converting data that can be considered as information if interpreted correctly. In order to find some statistically relevant information from data, it is important to have mechanisms for reducing the information of each segment in the audio signal into features. These features should describe each segment in such a characteristic way that other similar segments can be grouped together by comparing their features. Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. This paper deals with result obtained by MFCC and LPC feature extraction technique and SVM feature matching technique.

Design and Development of Database and Automatic Speech Recognition System for Travel Purpose in Marathi