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Identification of Ragas in Hindustani Classical Music Using Aaroha and Avaroha Dr

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Identification of Ragas in Hindustani Classical Music Using Aaroha and Avaroha Dr International Journals of Advanced Research in Research Article June Computer Science and Software Engineering 2017 ISSN: 2277-128X (Volume-7, Issue-6) Identification of Ragas in Hindustani Classical Music Using Aaroha and Avaroha Dr. D. M. Chandwadkar* Dr. M. S. Sutaone K. K. Wagh Institute of Engineering Government College of Engineering, Education & Research, Nashik, India Pune, Maharashtra, India DOI: 10.23956/ijarcsse/V7I6/0335 Abstract— Hindustani Classical Music is one of the oldest music cultures still being performed actively. Despite of the advancements in the technologies related to music analysis, very little has been tried related to the expressiveness of Hindustani Classical Music. Ragas are the central structure of Hindustani classical music. Raga can be thought of as the sequential arrangement of notes that is capable of invoking the emotion of a song. In this paper we have tried to identify eighteen ragas played by three string instruments: Santoor, Sarod and Sitar using signal processing techniques. A database consisting of recorded Aaroha and Avaroha of these 18 ragas played by three performers is used as input to the system. The notes present in the audio file are obtained using Harmonic Product Spectrum method of pitch detection. Using this technique we could achieve about 85% accuracy. This shows that our approach, though simple, is effective in solving the problem. Keywords— Hindustani Classical Music, Raga recognition, Aaroha-Avaroha, Swara, Pitch, Harmonic Product Spectrum I. INTRODUCTION Hindustani Classical Music is one of the oldest musical traditions in the world. The subject of classical Indian music is rich, with its historical, cultural, aesthetic, theoretical, and performing facets. For the past fifty years, due to the emigration of Indians and the popularity of Indian artists, it has become widely known to international audience. Ragas are the building blocks of Hindustani classical music. In its simplest description a Raga is a collection of notes. Actually, they are a lot more than just a collection of notes. Ragas are the melodic modes on which a Hindustani musical performance is based. RAGA: The Melodic Framework The most fundamental melodic concept in Hindustani classical music is raga. Raga is a melodic abstraction around which almost all Hindustani classical music is organized. Raga, in the Sanskrit dictionary, is defined as "the act of coloring or dyeing" (the mind in this context) and "any feeling or passion especially love, affection, sympathy, vehement desire, interest, joy, or delight". In music, these descriptions apply to the impressions of melodic sounds on both the artist(s) and listener(s). A raga consists of required and optional rules governing the melodic movements of notes within a performance. The term, Raga, first occurred in a technical context in the Brihaddeshi [1] where it is described as "That which is a special dhwani (tune), is bedecked with swara (notes) and varna and is colorful or delightful to the minds of the people, is said to be rāga". Hence, raga is neither a tune nor a scale; it is a set of rules which can together be called a melodic framework. The rules of a raga can be defined by The list of specific notes (swaras) that can be used during playing of the raga The manner in which the notes are used, i.e. specific ways of ornamenting notes or emphasizing/de-emphasizing them Manner in which the scale is ascended (Aaroha) or descended (Avaroha) Optional or required musical phrases, the way in which to reveal these phrases, and/or combine them The octave or frequency range to emphasize The relative pacing between the notes The time of day and/or season when the raga may be performed so as to invoke the emotions of the raga for maximum impact on the mental and emotional state of the performer and listener Observance of these rules during the performance of a raga does not aspire to be purely a technical or intellectual exercise, but also to evoke the rasa or bhava (the experience, mood, emotion, or feeling) of the raga in both the artist and the listener. A raga is best experienced rather than analyzed. Any raga can be characterized by: Aaroha (ascending sequence of notes) and Avaroha (descending sequence of notes), the set of unique notes in these sequences (scale), Jaati of raga (number of notes in Aaroha and Avaroha), the most stressed note (Vadi swara), the second most stressed note (Samwadi swara), the notes that are not allowed (Varjit swara), pakad (catch/characteristic phrase): a set of one or two sequences and Thaat (scale type: swaras that make a raga). © www.ijarcsse.com, All Rights Reserved Page | 805 Chandwadkar et al., International Journals of Advanced Research in Computer Science and Software Engineering ISSN: 2277-128X (Volume-7, Issue-6) In Hindustani music, swaras are the seven notes in the scale, denoted by Sa, Re, Ga, Ma, Pa, Dha and Ni. These are called as Shuddha (pure) swaras. Sa and Pa are fixed swaras. The rest are mutable swaras and each has one 'vikrut' (different) version. The 5 vikrut swaras have two variations each (komal 're', 'ga', 'dha', 'ni', and teevra /sharp 'ma'), which account for 12 notes in an octave. We use the symbols S, R, G, M, P, D, N for notating shuddha Sa, Re, Ga, Ma, Pa, Dha, Ni respectively. For notating komal Re, Ga, Dha, Ni we use symbols r, g, d, n respectively and M’ for tivra Ma. This document is a template. An electronic copy can be downloaded from the Journal website. For questions on paper guidelines, please contact the journal publications committee as indicated on the journal website. Information about final paper submission is available from the conference website. II. RAGA RECOGNITION Very little work has been done in the area of applying techniques from computational musicology and artificial intelligence to Hindustani classical music. In order to identify ragas computationally, swara intonation, scale, note progressions and pakad/characteristic phrases are used. Sahasrabudde et al [2] model the raga as finite automata which were constructed using information codified in standard texts on classical music. A finite automata has a set of states between which the transitions take place. This approach was used to generate new samples of the Raga, which were technically correct and were indistinguishable from compositions made by humans. Pandey et al [3] use HMM models to recognize the ragas. They used Aaroha and Avaroha for identification of ragas and the results were complemented with scores obtained from two pakad matching modules. The approach was tested on two ragas. Rajeswari et al [4] recognized ragas by estimating the scale from the given tune and by comparing it with template scales. Their test data consists of 30 tunes in 3 ragas sung by 4 artists. They use the harmonic product spectrum algorithm to extract the pitch. The results obtained show 67% accuracy. Shetty et al [5] use a similar approach for raga recognition. They used the individual swaras used in Aaroha-Avaroha. Neural networks were used for classification. They report an accuracy of 95% over 90 tunes from 50 ragas, using 60 tunes as training data and the remaining 30 tunes as test data. Sinith et al [6] also used HMMs of ragas to search for musical patterns in a catalogue of monophonic Carnatic music. They build models for 6 typical music patterns corresponding to 6 ragas. They report 100% accuracy in identifying an unknown number of tunes into 6 ragas. P. Chordia and A. Rae [7] use pitch class profiles and bi-grams of pitches to classify ragas. 17 ragas played by a single artist on sarod are used as data. They also use the harmonic product spectrum algorithm to extract the pitch. They have shown that bi-grams are useful in discriminating the ragas with the same scale. Belle et al [8] used swara intonation to differentiate ragas that share the same scale intervals. They evaluated the system on 10 tunes, with 4 ragas evenly distributed in 2 distinct scale groups. A detailed survey of computational analysis of Indian classical music related to automatic recognition of ragas is presented by Koduri et al [9]. III. INSTRUMENTS USED A string instrument is a musical instrument that produces sound with vibrating strings amplified by one or more of the three main methods: Vibration of a sounding board via a bridge Resonance of air in a sound box, often through a sound hole Electric pickup for an instrument amplifier driving a loudspeaker The Indian Santoor is an ancient string musical instrument native to Jammu and Kashmir, with origins in Persia. The Santoor is a trapezoid-shaped hammered dulcimer often made of walnut, with seventy two strings [10]. In ancient sanskrit texts, it has been referred to as Shatatantri vina (100-stringed vina). The special-shaped mallets are lightweight and are held between the index and middle fingers. A typical Santoor has two sets of bridges, providing a range of three octaves. The Indian Santoor is more rectangular and can have more strings than the Persian counterpart, which generally has 72 strings. The instrument currently available in the market has 87 strings, clubbed in 29 sets each consisting of 3 strings. The sitar is a plucked stringed instrument used mainly in Indian classical music. It is used mainly in India and to some extent in neighboring countries. The name "Sitar" in Persian means "Sè" (Three) and "Tār" (String Pairs) hence it has the name "Sitar" although a typical sitar used in India has 17-25 strings. It derives its resonance from sympathetic strings, a long hollow neck and a gourd resonating chamber. It is also said that Sitar is derived from an Indian instrument called Veena [10].
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