Emotional responses to Hindustani raga music: the role of musical structure

In Indian classical music, ragas constitute specific combinations of tonic intervals potentially capable of evoking distinct emotions. A raga composition is typically presented in two modes, namely, alaap and gat. Alaap is the note by note delineation of a raga bound by a slow tempo, but not bound by a rhythmic cycle. Gat on the other hand is rendered at a faster tempo and follows a rhythmic cycle. Our primary objective was to (1) discriminate the emotions experienced across alaap and gat of ragas, (2) investigate the association of tonic intervals, tempo and rhythmic regularity with emotional response. 122 participants rated their experienced emotion across alaap and gat of 12 ragas. Analysis of the emotional responses revealed that (1) ragas elicit distinct emotions across the two presentation modes, and (2) specific tonic intervals are robust predictors of emotional response. Specifically, our results showed that the ‘minor second’ is a direct predictor of negative valence. (3) Tonality determines the emotion experienced for a raga where as rhythmic regularity and tempo modulate levels of arousal. Our findings provide new insights into the emotional response to Indian ragas and the impact of tempo, rhythmic regularity and tonality on it

The Pitch Histogram of Traditional Chinese Anhemitonic Pentatonic Folk Songs

Funding Information: The APC was funded by Open Access Initiative of the University of Bremen and the DFG via SuUB Bremen. Publisher Copyright: © 2022 by the authors.As an essential subset of Chinese music, traditional Chinese folk songs frequently apply the anhemitonic pentatonic scale. In music education and demonstration, the Chinese anhemitonic pentatonic mode is usually introduced theoretically, supplemented by music appreciation, and a non-Chinese-speaking audience often lacks a perceptual understanding. We discovered that traditional Chinese anhemitonic pentatonic folk songs could be identified intuitively according to their distinctive bell-shaped pitch distribution in different types of pitch histograms, reflecting the Chinese characteristics of Zhongyong (the doctrine of the mean). Applying pitch distribution to the demonstration of the Chinese anhemitonic pentatonic folk songs, exemplified by a considerable number of instances, allows the audience to understand the culture behind the music from a new perspective by creating an auditory and visual association. We have also made preliminary attempts to feature and model the observations and implemented pilot classifiers to provide references for machine learning in music information retrieval (MIR). To the best of our knowledge, this article is the first MIR study to use various pitch histograms on traditional Chinese anhemitonic pentatonic folk songs, demonstrating that, based on cultural understanding, lightweight statistical approaches can progress cultural diversity in music education, computational musicology, and MIR.publishersversionpublishe

From heuristics-based to data-driven audio melody extraction

The identification of the melody from a music recording is a relatively easy task for humans, but very challenging for computational systems. This task is known as "audio melody extraction", more formally defined as the automatic estimation of the pitch sequence of the melody directly from the audio signal of a polyphonic music recording. This thesis investigates the benefits of exploiting knowledge automatically derived from data for audio melody extraction, by combining digital signal processing and machine learning methods. We extend the scope of melody extraction research by working with a varied dataset and multiple definitions of melody. We first present an overview of the state of the art, and perform an evaluation focused on a novel symphonic music dataset. We then propose melody extraction methods based on a source-filter model and pitch contour characterisation and evaluate them on a wide range of music genres. Finally, we explore novel timbre, tonal and spatial features for contour characterisation, and propose a method for estimating multiple melodic lines. The combination of supervised and unsupervised approaches leads to advancements on melody extraction and shows a promising path for future research and applications

Characterization of intonation in Carnatic music by parametrizing pitch histograms

Intonation is an important concept in Carnatic music that/nis characteristic of a raaga, and intrinsic to the musical expression/nof a performer. In this paper we approach the description/nof intonation from a computational perspective,/nobtaining a compact representation of the pitch track of a/nrecording. First, we extract pitch contours from automatically/nselected voice segments. Then, we obtain a a pitch/nhistogram of its full pitch-range, normalized by the tonic/nfrequency, from which each prominent peak is automatically/nlabelled and parametrized. We validate such parametrization/nby considering an explorative classification task:/nthree raagas are disambiguated using the characterization/nof a single peak (a task that would seriously challenge a/nmore na¨ıve parametrization). Results show consistent improvements/nfor this particular task. Furthermore, we perform/na qualitative assessment on a larger collection of raagas,/nshowing the discriminative power of the entire representation./nThe proposed generic parametrization of the intonation/nhistogram should be useful for musically relevant/ntasks such as performer and instrument characterization.This research was partly funded by the European Research/nCouncil under the European Union’s Seventh Framework/nProgram, as part of the CompMusic project (ERC grant/nagreement 267583). JS acknowledges JAEDOC069/2010/nfrom Consejo Superior de Investigaciones Cient´ıficas, 2009-/nSGR-1434 from Generalitat de Catalunya, TIN2009-13692-/nC03-01 from the Spanish Government, and EU Feder Funds

Characterization of intonation in Carnatic music by parametrizing pitch histograms

Intonation is an important concept in Carnatic music that/nis characteristic of a raaga, and intrinsic to the musical expression/nof a performer. In this paper we approach the description/nof intonation from a computational perspective,/nobtaining a compact representation of the pitch track of a/nrecording. First, we extract pitch contours from automatically/nselected voice segments. Then, we obtain a a pitch/nhistogram of its full pitch-range, normalized by the tonic/nfrequency, from which each prominent peak is automatically/nlabelled and parametrized. We validate such parametrization/nby considering an explorative classification task:/nthree raagas are disambiguated using the characterization/nof a single peak (a task that would seriously challenge a/nmore na¨ıve parametrization). Results show consistent improvements/nfor this particular task. Furthermore, we perform/na qualitative assessment on a larger collection of raagas,/nshowing the discriminative power of the entire representation./nThe proposed generic parametrization of the intonation/nhistogram should be useful for musically relevant/ntasks such as performer and instrument characterization.This research was partly funded by the European Research/nCouncil under the European Union’s Seventh Framework/nProgram, as part of the CompMusic project (ERC grant/nagreement 267583). JS acknowledges JAEDOC069/2010/nfrom Consejo Superior de Investigaciones Cient´ıficas, 2009-/nSGR-1434 from Generalitat de Catalunya, TIN2009-13692-/nC03-01 from the Spanish Government, and EU Feder Funds