Vijay Kiran Battula and Appala Naidu Gottapu
Jawaharlal Nehru Technological University, India

Presence of noise increases the dimension of the information. A noise suppression algorithm is developed with an idea of combining the General Kalman Filter and Estimate Maximization (EM) frame work.This combination is helpful and effective in identifying noise characteristics of an acoustic environment. Recursion between Estimate step and Maximization step enabled the algorithm to deal any model of noise. The same Speech enhancement procedure in applied in the pre-processing stage of a conventional Speakeridentification method. Due to the non-stationary nature of noise and speech adaptive algorithms are required. Algorithm is first applied for Speech enhancement problem and then extended to using it in the pre-processing step of the Speaker identification. The present work is compared in terms of significant metrics with existing and popular algorithms and results show that the developed algorithm is dominantover them

Speech processing, Speech enhancement, Speaker identification, General Kalman filter and EM algorithm