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Doctoral Thesis / Dissertation from the year 2019 in the subject Musicology - Miscellaneous, grade: NA, , language: English, abstract: The aim of the research work presented in this book, is to find important features of the music signal so that we can classify the raga into different category. It will encourage the scientific research in Indian Classical music, specifically Hindustani music. The main objectives of the study include: . Extraction of features of a music signal which are relevant for classification of the music signal using different techniques. . To determine whether the…mehr

Produktbeschreibung
Doctoral Thesis / Dissertation from the year 2019 in the subject Musicology - Miscellaneous, grade: NA, , language: English, abstract: The aim of the research work presented in this book, is to find important features of the music signal so that we can classify the raga into different category. It will encourage the scientific research in Indian Classical music, specifically Hindustani music. The main objectives of the study include: . Extraction of features of a music signal which are relevant for classification of the music signal using different techniques. . To determine whether the artists singing the raga during a concert belongs to same gharana or different gharanas by finding the MFCC (Mel frequency cepstral co-efficients ) features of a music signal. Andrew plot is used to study the results. . Comparison between two types of ragas, one being aesthetically known to be restful raga and the other restless in nature is done by finding statistical features. Distinction between the two types of raga is done by finding the mean, standard deviation and Inter onset interval. The Transitory and non-transitory frequency movements between the notes of both ragas is determined. . Statistical Modeling of ragas is done to distinguish between Restful ragas and Restless Ragas. Simple Exponential smoothing techniques is used for Modeling the Restless Ragas Pilu and Bhairavi and Double exponential Smoothing techniques is used for Modeling the Restful Raga Todi . . The work is focused on music emotion representation. The characteristics features of music signal such as rhythm, melody, pitch and timbre are studied. Among these which parameter(s) play a major role in creating happy or sad emotion in the song or music samples are studied.

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Autorenporträt
Dr. Soubhik Chakraborty, an M.Sc. (Statistics), PhD (Science) and NET (UGC/CSIR) in Mathematical Sciences, is currently serving as the Professor & Head, Department of Mathematics at Birla Institute of Technology, Mesra, Ranchi, India. His research interests are algorithm analysis, music analysis and statistical computing. He has published several books, research monograms and research papers in peer reviewed journals of international and national repute in these areas apart from guiding several research scholars leading to PhD. He is also an acknowledged reviewer associated with ACM, AMS and IEEE. He has been a visiting scientist twice to Indian Statistical Institute (Bangalore Centre in 2002, Kolkata Centre in 2004, the latter under INSA fellowship). He is a leading figure in computational musicology and has written the first book on the topic (in the context of Hindustani music; see ref [1] in relevant publications). He has been the principal investigator of a UGC major research project titled Analyzing the structure and performance of Hindustani classical music through statistics in his institute. He has received several awards in both teaching and research including the National Award for Teaching Excellence (Mathematics) given by Indus Foundation (2013) and the Best Academic Researcher Award 2013 given by Association of Scientists, Developers and Faculties (2013). Prior to joining this institute in 2006 (Nov 30), he served as a lecturer in Statistics at T.M. Bhagalpur university where he taught Statistics at both undergraduate and postgraduate levels for about ten years. Relevant Publications (books):- 1. Soubhik Chakraborty, Guerino Mazzola, Swarima Tewari and Moujhuri Patra, Computational Musicology in Hindustani Music, Springer, 2014 2. Asoke Kumar Datta, Sandeep Singh Solanki, Ranjan Sengupta, Soubhik Chakraborty, Kartik Mahto, Anirban Patranabis, Signal Analysis of Hindustani Classical Music, Springer, 2017 3. Shashi Bhushan Singh, Soubhik Chakraborty, Keashav Mohan Jha, Satish Chandra, Shanti Prakash and Swarima Tewari, Music and Medicine: Healing Brain Injury through Ragas, CBH publications, 2016