Ragas are characterized by their melodic motifs or catch phrases that constitute strong cues to the raga identity for both, the performer and the listener, and therefore are of great interest in music retrieval and automatic transcription. While the characteristic phrases, or pakads, appear in written notation as a sequence of notes, musicological rules for interpretation of the phrase in performance in a manner that allows considerable creative expression, while not transgressing raga grammar, are not explicitly defined. In this work, machine learning methods are used on labeled databases of Hindustani and Carnatic vocal audio concerts to obtain phrase classification on manually segmented audio. Dynamic time warping and HMM based classification are applied on time series of detected pitch values used for the melodic representation of a phrase. Retrieval experiments on ragacharacteristic phrases show promising results while providing interesting insights on the nature of variation in the surface realization of raga-characteristic motifs within and across concerts.

This article 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 tāl. 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 tāl cycle.

A prominent aspect of the notion of musical similarity across the music of various cultures is related to the local matching of melodic motifs. This holds for Indian art music, a highly structured form with raga playing a critical role in the melodic organization. Apart from the tonal material, a raga is characterized by a set of melodic phrases that serve as important points of reference in a music performance. Musicians acquire in their training a knowledge of the melodic phrase shapes or motifs particular to a raga and the proficiency to render these correctly in performance. This phenomenon of learned schema might be expected to influence the musicians' perception of variations of the melodic motif in terms of pitch contour shape. Motivated by the parallels between the musical structure and prosodic structure in speech, identification and discrimination experiments are presented, which explore the differences between trained musicians' (TMs) and non-musicians' perception of ecologically valid synthesized variants of a raga-characteristic motif, presented both in and out of context. It is found that trained musicians are relatively insensitive to acoustic differences associated with note duration in the vicinity of a prototypical phrase shape while also clearly demonstrating the heightened sensitivity associated with categorical perception in the context of the boundary between ragas.

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Raga grammar provides a theoretical framework that supports creativity and flexibility in improvisation while carefully maintaining the distinctiveness of each raga in the ears of a listener. A computational model for raga grammar can serve as a powerful tool to characterize grammaticality in performance. Like in other forms of tonal music, a distributional representation capturing tonal hierarchy has been found to be useful in characterizing a raga's distinctiveness in performance. In the continuous-pitch melodic tradition, several choices arise for the defining attributes of a histogram representation of pitches. These can be resolved by referring to one of the main functions of the representation, namely to embody the raga grammar and therefore the technical boundary of a raga in performance. Based on the analyses of a representative dataset of audio performances in allied ragas by eminent Hindustani vocalists, we propose a computational representation of distributional information, and further apply it to obtain insights about how this aspect of raga distinctiveness is manifested in practice over different time scales by very creative performers.