A behavioral study of emotions in south indian classical music andits implications in music recommendation systems

Koduri, Gopala Krishna; Indurkhya, Bipin

doi:10.1145/1878061.1878079

Cited by 12 publications

(2 citation statements)

References 9 publications

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“…This rating scale, proposed by author, has been adopted from Koduri and Indurkhya (2010) and Misra (2014). It has 11 rasa (with clusters of emotions) to be rated on seven-point scale.…”

Section: Music Emotion Scalementioning

confidence: 99%

Exploring the nature of music engagement and its relation to personality among young adults

Upadhyay

Shukla

Tripathi

et al. 2017

International Journal of Adolescence and Youth

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“…This rating scale, proposed by author, has been adopted from Koduri and Indurkhya (2010) and Misra (2014). It has 11 rasa (with clusters of emotions) to be rated on seven-point scale.…”

Section: Music Emotion Scalementioning

confidence: 99%

Exploring the nature of music engagement and its relation to personality among young adults

Upadhyay

Shukla

Tripathi

et al. 2017

International Journal of Adolescence and Youth

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“…The raga of a music is the primary element considered for music therapy. There are various ragas that can be used for different purposes, for example, Ahirbhairav and Todi are used for hypertension, Punnagavarali is used to control anger and violence, Todi is used to relief from cold and headache, Shivaranjani is used for memory related problems, Bhairavi is used to get relief from sinus, cold, phlegm, tooth ache etc [12]. Similarly, Chandrakauns raga is used to treat the heart problems and diabetes, Darbari is used to reduce the tension and to provide relaxation [12].…”

Section: Introductionmentioning

confidence: 99%

An Approach to Discover Similar Musical Patterns

Chakrabarty

Islam²,

Pricop

et al. 2022

IEEE Access

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An algorithm has been developed to find the similarity between given songs. The song pattern similarity has been determined by knowing the note structures and the fundamental frequencies of each note of the two songs, under consideration. The statistical concept namely Correlation of Coefficient is used in this work. Correlation of Coefficient is determined by applying 16 Note-Measure Method. If Correlation of Coefficient is near to 1, it indicates that the patterns of the two songs under consideration are similar. Otherwise, there exists a certain percentage of similarity only. This basic principle is used in a set of Indian Classical Music (ICM) based songs. The proposed algorithm can determine the similarity between songs, so that alternative songs in place of some well-known songs can be identified, in terms of the embedded raga patterns. A digital music library has been constructed as a part of this work. The library consists of different songs, their raga name, and their corresponding healing capabilities in terms of music therapy. The proposed work may find application in the area of music therapy. Music therapy is an area of research which is explored significantly in recent time. This work can also be exploited for developing intelligent multimedia tool that is applicable in healthcare domain. A multimedia based mobile app has been developed encapsulating the above mentioned idea that can recommend alternative or similar songs to the existing ICM based songs. This mobile app based music recommendation system may be used for different purposes including entertainment and healthcare. As a result of the applications of the proposed algorithm, similar songs in terms of raga patterns can be discovered from within the pool of a set of songs. A music recommendation system built on this algorithm can retrieve an alternative song from within the pool of songs as a replacement to a wellknown song, which otherwise may be used for a particular music therapy. Results are reported and analyzed thoroughly. Future scope of the work is outlined.INDEX TERMS Fundamental frequency measure (FFM), correlation of coefficient, computational musicology, music recommendation system (MIR), music therapy, electronic healthcare.

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Genre Based Classification of Hindi Music

Chaudhary

Singh

2019

Advances in Intelligent Systems and Computing

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A behavioral study of emotions in south indian classical music andits implications in music recommendation systems

Cited by 12 publications

References 9 publications

Exploring the nature of music engagement and its relation to personality among young adults

Exploring the nature of music engagement and its relation to personality among young adults

An Approach to Discover Similar Musical Patterns

Genre Based Classification of Hindi Music

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