ABSTRACT:In this article, we present an efficient two-pass search strategy for the implementation of a Hidden Markov Model (HMM)-based music identification system. In our previous work, we demonstrated a single-pass HMM-based music identification system, considering its application to music copyright protection. This conventional system showed very robust performance to signal-level variations between perceptually identical music files. However, it requires heavy computation for search. In the proposed two-pass search system, the conventional single-pass search is extended to two-pass. In pass 1 of the proposed method, a queried music produces an accumulated band energy histogram which is a set of normalized sums of band energies for each frequency bin. This histogram is compared to all of the histograms for the registered music files. The system generates a list of small number of most probable music files among the all of the registered music files. In pass 2, HMM-based search is applied only to candidate music files selected in pass 1. Using the proposed two-pass strategy, we successfully implemented a HMM-based music identification system, which maintains the same level robustness to signal level variations between perceptually identical music files but also produces the identification result very quickly.