A robust multilevel speech verification wavelet decomposition for inadequate training data sets of mobile device systems

Abstract

With the development of speech signal processing, universality, easy collection and personal speech signal uniqueness, many researchers are attracted to the field of speech verification. Most of the current speech verifications are based on long training data sets in order to achieve good results, and there are no good verification schemes in case of inadequate training data sets. This paper proposes a novel architecture for speech verification using a multilevel method, which extracts feature parameters through a multiple wavelet transform for mobile phone voice. The experiments show that the multilevel wavelet authentication architecture improves performance in speech verification. The recognition rate of the mobile phone system is more robust and superior to other methods.