Similar Segment Detection for Music Structure Analysis via Viterbi Algorithm

The analysis of audio signals of popular and rock songs of the verse-chorus form to reconstruct its original musical structures is investigated in this work. We first compute the similarity degree between any two measures in a song based on selected features and represent these numbers in a measure-based similarity matrix. Then, we study the similarity across a sequence of consecutive measures, which is revealed by straight segments in parallel with the diagonal line of the similarity matrix. Generally, chorus parts have higher similarity values while verse parts have lower similarity values. As a result, the verse parts are difficult to detect in the presence of the chorus parts. To tackle this problem systematically, the Viterbi Algorithm is adopted to find optimal paths in the lower-triangular similarity matrix, which represent repetitive segments of both choruses and verses. Finally, several post-processing steps are developed to decode the music structure into the verse, the chorus and other non-repetitive parts. Experimental results obtained from several musical audio data are shown to demonstrate the performance of the proposed method.