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ENHANCEMENT OF RECOGNITION ACCURACY OF AUTOMATIC SPEAKER RECOGNITION SYSTEM IN NOISY ENVIRONMENTS

In this Thesis two wavelet based methods (TADWT and SSWPT) for enhancement of noisy speech are developed and reported. The effectiveness of the reported speech enhancement techniques is evaluated by means of speaker recognition under noisy conditions. The automatic speaker recognition technologies have been developed into more and more important modern technologies required by many speech-aided applications. The practical implementation of speaker recognition technologies on handheld devices or the internet, faces many challenges. One of these is environmental noise. A new ASR system is developed and presented which aims to provide the robustness at the signal level using the TADWT and SSWPT speech enhancement methods as a front end processing stage to improve the speaker specific features and hence speaker recognition performance in noisy environment. The comparative analysis made based on extracting features and speaker modeling, to get improvement in recognition accuracy.