Adult Voice Recognition System using Text Variable Phoneme Model and Coarse Speaking Fundamental Frequency Characteristics

-------------------------------------------------------Abstract--------------------------------------------------------Speech recognition is a fascinating application of Digital Signal Processing and has many real-world applications. In this paper, a speech recognition system is developed for isolated spoken words using Discrete Wavelet Transforms (DWT) and Artificial Neural Networks (ANN). Speech signals are one-dimensional and are random in nature. This paper investigates Automatic Speech Recognition of gender from speech segments using digital speech processing and pattern recognition techniques. Speaker recognition is an automatic process of recognizing the user on the basis of unique information carried by speech waves. The voice of the speaker is used to verify his or her identity and provide control for access to various services such as, voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers using Speaker recognition technique. Acoustic coefficients were used to form test and reference templates for vowels, voiced and unvoiced fricatives. The effects of different distance measures were comparatively assessed to determine their effectiveness for the task of gender recognition from speech segments. Daubechies wavelets are and a multi-layer neural network trained with back propagation training algorithm is used for classification purpose