Abstract
This paper provides insights into aspects of tempo and rhythmic elaboration in Hindustani music, based on a study of a large corpus of recorded performances. Typical tempo developments and stress patterns within a metrical cycle are computed, which we refer to as tempo and rhythm patterns, respectively. Rhythm patterns are obtained by aggregating spectral features over metrical cycles. They reflect percussion patterns that are frequent in the corpus, and enable a discussion of the relation between such patterns and the underlying metrical framework, the taal. Tempo patterns, on the other hand, are computed using reference beat annotations. They document the dynamic development of tempo throughout a metrical cycle, and reveal insights into the flexibility of time in Hindustani music for the first time using quantitative methods on a large set of performances. Focusing on aspects of tempo and rhythm, we demonstrate the value of a computational methodology for the analysis of large music corpora by revealing the range of tempi used in performances, intra-cycle tempo dynamics and percussion accents at different positions of the taal cycle.
Highlights
Recent advances in digital humanities have brought forward aspects of human behavior using large corpora
Performance analysis of music corpora can provide us with several insights into different aspects of music and show us the contrasts and similarities between music theory and practice
Another study with focus on syncopation was performed by Huron and Ommen (2006), who document the development of syncopation in American popular music in periods until 1939
Summary
Recent advances in digital humanities have brought forward aspects of human behavior using large corpora. Corpus studies are in general driven by the common motivation of contributing empirical results that improve the understanding of a specific property of data in the corpus In music, typically, these properties are melody, harmony, and rhythm. Within the CompMusic project, methods for the analysis of five specific music cultures were developed, and Serra (2014) introduces the corpora that were compiled for the evaluation of these tools. Kroher et al (2015) present a corpus of Spanish Flamenco music They adopt the criteria as developed by Serra (2014) and compile a corpus of 95 h of audio recordings, along with metadata regarding artist and style. We demonstrate how a corpus that originally targeted development in audio processing can be applied to the analysis of structures in music performances, with results relevant to research in the musicologies and digital humanities
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