The meter of a musical excerpt provides high-level rhythmic information and is valuable in many music information retrieval tasks. We investigate the use of a computationally efficient approach to metrical analysis based on psycho-acoustically motivated decomposition of the audio signal. A two-stage comb filter-based approach, originally proposed for double/ triple meter estimation, is extended to a septuple meter (such as 7/8 time-signature) and its performance evaluated on a sizable Indian music database. We find that this system works well for Indian music and the distribution of musical stress/accents across a temporal grid can be utilized to obtain the metrical structure of audio automatically. © 2012 Springer-Verlag.
CITATION STYLE
Gulati, S., Rao, V., & Rao, P. (2012). Meter detection from audio for Indian music. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7172 LNCS, pp. 34–43). https://doi.org/10.1007/978-3-642-31980-8_3
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