Abstract
Perceptual audio coding is a novel approach to compress audio by taking advantage of models of the human auditory system also known as psychoacoustic models. The quality and efficiency of the encoding process depends highly on how these models accurately characterize the nature of the audio signal, in particular its tonality attributes. This paper explores various analysis techniques using wavelet packet tree decomposition to accurately estimate tonality by exploiting energy and statistical information. More specifically, the tonality estimation is based on the correlation information of the nodes and uses wavelets such as Haar and Daubechies 1 for decomposing the signal.