Soubhik Chakraborty – författare

The book opens with a short introduction to Indian music, in particular classical Hindustani music, followed by a chapter on the role of statistics in computational musicology. The authors then show how to analyze musical structure using Rubato, the music software package for statistical analysis, in particular addressing modeling, melodic similarity and lengths, and entropy analysis; they then show how to analyze musical performance. Finally, they explain how the concept of seminatural composition can help a music composer to obtain the opening line of a raga-based song using Monte Carlo simulation.  The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.

The book opens with a short introduction to Indian music, in particular classical Hindustani music, followed by a chapter on the role of statistics in computational musicology. The authors then show how to analyze musical structure using Rubato, the music software package for statistical analysis, in particular addressing modeling, melodic similarity and lengths, and entropy analysis; they then show how to analyze musical performance. Finally, they explain how the concept of seminatural composition can help a music composer to obtain the opening line of a raga-based song using Monte Carlo simulation.  The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.

Academic Paper from the year 2020 in the subject Musicology - Systematic musicology, , course: IMSc Mathematics and Computing, language: English, abstract: With an onset of electronic commerce and portable devices for communication, cryptology has become an exceedingly important science in the present day. The diversity of applications in which crypto-algorithms have to operate have increased and hence the requirement for the efficient algorithms have grown. Confidential information of a government or private agency or department is secured through the use of Cryptography. Musical properties, for example, notes of which the music is made are not consistent and shift from one arrangement to another. Same tune played by various composers shows a variety in the succession of notes utilized along with different qualities of a musical organization, for example, term of each note and the recurrence at which each note is played. Such a variety can be utilized to encode the message. In this work, we have joined the utilization of Hindustani (North Indian) melodic notes to encode messages and used this method on three ragas to test the robustness of the algorithm with different input size. We have utilized a semi-natural composition procedure to produce note successions of Indian music which would then be able to be utilized as a device for message stowing away. This from the outset place guarantees that the message is avoided the interloper and second it gives another irregular arrangement of notes each time same message is sent. So the very motivation behind a Cryptographic calculation is served. The scrambled message as melodic notes is at that point sent to the planned beneficiary as a melodic structure which helps in opposing the gatecrasher of detecting any classified data that is being sent over the correspondence channel.

Research Paper (postgraduate) from the year 2021 in the subject Musicology - Miscellaneous, grade: 8.0, , course: IMSc Mathematics and Computing, language: English, abstract: This work gives a comprehensive overview of research on the multidisciplinary field of Music Information Retrieval (MIR). MIR uses knowledge from areas as diverse as signal processing, machine learning, information and music theory. The Main Feature of this work is to explore how this knowledge can be used for the development of novel methodologies for browsing and retrieval on large music collections, a hot topic given recent advances in online music distribution and searching. Emphasis would be given to audio signal processing techniques. Music information retrieval (MIR) is the interdisciplinary science of retrieving information from music. MIR is a small but growing field of research with many realworld applications. Those involved in MIR may have a background in musicology, sychoacoustics, psychology, academic music study, signal processing, informatics, machine learning, optical music recognition, computational intelligence or some combination of these. MIR is being used by businesses and academics to categorize, manipulate and even create music. One of the classical MIR research topics is genre classification, which is categorizing music items into one of pre-defined genres such as classical, jazz, rock, etc. Mood classification, artist classification, and music tagging are also popular topics.

Master's Thesis from the year 2022 in the subject Mathematics - Statistics, grade: 9.0, , course: IMSc Mathematics and Computing, language: English, abstract: In any application that involve data, outlier detection is critical. In the data mining and statistics literature, outliers are sometimes known as abnormalities, discordants, deviants, or anomalies. The data in most applications are generated by one or more generating processes, which may reflect system activity or observations about entities. This monograph explains what an outlier is and how it can be used in a variety of industries in the first chapter of the report. This chapter also goes over the various types of outliers. Outlier analysis is an important part of research or industry that involves a large amount of data, as described in Chapter 2; it also describes how outliers are related to different data models. Chapter 3 covers Univariate Outlier Detection and methods for completing this task. Multivariate Outlier Detection techniques such as Mahalanobis distance and isolation forest are covered in Chapter 4. Finally, in Chapter 5, the Python programming language has been used to analyse and detect existing outliers in a public dataset. We hope this monograph would be useful to students and practitioners of statistics and other fields involving numerical data analytics.

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.

Master's Thesis from the year 2019 in the subject Mathematics - Stochastics, grade: 8.5, , course: Integrated MSc in Mathematics and Computing, language: English, abstract: We are interested in the behaviour of a determinant with i.i.d. random variates as its elements. A probabilistic analysis has been done for such determinants of orders 2 and 3. We have considered some of the well known distributions, namely, discrete uniform, Binomial Poisson, continuous uniform, standard normal, standard Cauchy and exponential. We are able to give fiducial limits for the determinant using Chebyshev's inequality for all the distributions discussed in the text (except standard Cauchy distribution for which expectation does not exist). The main objective is to find the probability distribution of the determinant when its elements are from any of the distributions stated above. The desired distribution has been approximated using the method of transformation in general but when this method could not produce desired results we relied on empirical results based on simulation.

Master's Thesis from the year 2019 in the subject Musicology - Miscellaneous, grade: 8.5, , language: English, abstract: The present work attempts to study the impact of Hindustani Classical Music on Bollywood in a legitimate manner using a statistical approach emphasizing on statistical modeling of musical structure and performance and other statistical features such as note duration and inter onset interval with a case study in raga Yaman. Any music originates in the society and develops with the changing realities of it. It accepts new and modifies the existing cultural norms in different periods of time. This process of acceptance and rejection makes any form of art exist for long. Inspite of all this, in various phases, Hindustani classical music, being the base of many popular Bollywood songs has helped in their popularity and lifelong existence because of the strong focus on melody. A raga, which is the nucleus of Indian classical music, be it Hindustani or Carnatic, is a melodic structure with fixed notes and a set of rules which characterize a certain mood conveyed by erformance. Hindustani ragas have embraced the elements of several Bollywood songs, which has given these songs a strong impact despite the strong influence of western art music in Bollywood music industry. The present work attempts to study this impact in a legitimate manner using a statistical approach emphasizing on statistical modeling of musical structure and performance and other statistical features such as note duration and inter onset interval with a case study in raga Yaman. It turns out that the same statistical model for both the raga bandishand a song based on the same raga, i.e., Yaman, an evening raga of the Kalyan thaat.

This book presents a comprehensive overview of the basics of Hindustani music and the associated signal analysis and technological developments. It begins with an in-depth introduction to musical signal analysis and its current applications, and then moves on to a detailed discussion of the features involved in understanding the musical meaning of the signal in the context of Hindustani music. The components consist of tones, shruti, scales, pitch duration and stability, raga, gharana and musical instruments. The book covers the various technological developments in this field, supplemented with a number of case studies and their analysis. The book offers new music researchers essential insights into the use the automatic concept for finding and testing the musical features for their applications. Intended primarily for postgraduate and PhD students working in the area of scientific research on Hindustani music, as well as other genres where the concepts are applicable, it is also a valuable resource for professionals and researchers in musical signal processing.

This book presents a comprehensive overview of the basics of Hindustani music and the associated signal analysis and technological developments. It begins with an in-depth introduction to musical signal analysis and its current applications, and then moves on to a detailed discussion of the features involved in understanding the musical meaning of the signal in the context of Hindustani music. The components consist of tones, shruti, scales, pitch duration and stability, raga, gharana and musical instruments. The book covers the various technological developments in this field, supplemented with a number of case studies and their analysis. The book offers new music researchers essential insights into the use the automatic concept for finding and testing the musical features for their applications. Intended primarily for postgraduate and PhD students working in the area of scientific research on Hindustani music, as well as other genres where the concepts are applicable, it is also a valuable resource for professionals and researchers in musical signal processing.

This book presents a comprehensive overview of the basics of Hindustani music and the associated signal analysis and technological developments. It begins with an in-depth introduction to musical signal analysis and its current applications, and then moves on to a detailed discussion of the features involved in understanding the musical meaning of the signal in the context of Hindustani music. The components consist of tones, shruti, scales, pitch duration and stability, raga, gharana and musical instruments. The book covers the various technological developments in this field, supplemented with a number of case studies and their analysis. The book offers new music researchers essential insights into the use the automatic concept for finding and testing the musical features for their applications. Intended primarily for postgraduate and PhD students working in the area of scientific research on Hindustani music, as well as other genres where the concepts are applicable, it is also a valuable resource for professionals and researchers in musical signal processing.

As there can be more than one algorithm for the same problem, designing and analyzing an algorithm becomes important in order to make it as efficient and robust as possible. This book will serve as a guide to design and analysis of computer algorithms. Chapter One provides an overview of different algorithm design techniques and the various applications of such techniques. Chapter Two reviews the divide and conquer strategy and the algorithm types that employ it. Chapter Three explores greedy algorithms and some problems that can be solved with this approach. Chapter Four discusses in depth the dynamic programming approach. Chapter Five provides a solution to the N-Queens problem utilizing a backtracking approach. Chapter Six elucidates the reader to branch and bound techniques and provides three solutions to problems implementing them. Part II of this book begins with Chapter Seven, where two different approaches to the analysis of algorithms are discussed. Chapter Eight reviews randomized algorithms through an empirical lens. Chapter Nine discusses Master Theorem and the many kinds of problems this Theorem can solve. Chapter Ten, the final chapter, provides notes on the empirical complexity analysis of algorithms.

This book aims to educate the practitioner on pseudo-randomness in particular and discusses a few modern algorithms for random number generation. We attempt to describe what it means for a phenomenon to be random, discuss an approach to quantifying the amount of randomness and testing for statistical quality. A software testing suite is introduced to measure the performance and quality of arbitrary pseudo-random number generators, which are implemented in the V programming language.