Classification of Melodic Motifs in Raga Music with Time-series Matching

Abstract

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.

Phrase-based rĀga recognition using vector space modeling

“…A comparison of the results of M and S1 for each rāga reveals that their performance is complementary. M successfully recognizes several rāgas 5 Allied rāgas have a common set of svaras and similar melodic movement with high accuracy for which S1 performs poorly, and vice-versa. This suggests that the proposed phrase-based method can be combined with the pitch distribution-based methods to achieve a higher rāga recognition accuracy.…”

“…These challenges include the extraction of a reliable melodic representation, the lack of musically-meaningful melody segmentation models, the difficulty of deriving perceptually-relevant melodic similarity measures, and the ability to deal with large collections of long audio recordings. In recent years, research in computational modeling of IAM has been focused on addressing these challenges [4,5].…”

Analyzing Free-Hand Sound-Tracings of Melodic Phrases

“…Melodic contour is also used to describe the instrumentation of music from audio signals, for example in [36,37]. It is also interesting to note that melodic contour is used as the first step to identify musical structure in styles such as in Indian Classical music [38], and Flamenco [39].…”

Culture-Aware Approaches to Modeling and Description of Intonation Using Multimodal Data

“…Gulati et al [13] evaluate various tonic identification approaches over Indian art music traditions using diverse datasets under different conditions of the data (E.g., duration of the input audio clip, presence/absence of metadata etc). Rao et al [14] propose methods to classify melodic patterns in Indian art music and evaluate them using retrieval experiments.…”