Selection of the Best Wavelet Packet NodesBased on Mutual Information for Speaker Identification

摘要

The analysis of the speech signal using wavelet packet trees (WPT) is a very flexible tool, capable of effectively manipulate the frequency subbands thanks to the orthonormal bases it provides. Here, dimension reduction becomes very important since the number of sub-bands grows exponentially with the level of decomposition, and their discriminative relevancy is different, which leads to different resolution for each one. A method based on mutual information is proposed in order to keep as much discriminative information as possible and the less amount of redundant information.