This paper presents a general approach for the structural segmentation of songs. It is formalized as a cost optimization problem that combines properties of the musical content and prior regularity assumption on the segment length. A versatile implementation of this approach is proposed by means of a Viterbi algorithm, and the design of the costs are discussed. We then present two systems derived from this approach, based on acoustic and symbolic features respectively. The advantages of the regularity constraint are evaluated on a database of 100 popular songs by showing a significant improvement of the segmentation performance in terms of F-measure.