Soubhik Chakraborty's Books

Hindustani Classical Music

A Historical and Computational Study

By: Soubhik Chakraborty,Swarima Tewari,Arshi Rahman,Maria Jamal,Apra Lipi,Apoorva Chakraborty,Apoorva Nanda,Pranjala Shukla

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Hindustani Classical Music

A Historical and Computational Study

By: Soubhik Chakraborty,Swarima Tewari,Arshi Rahman,Maria Jamal,Apra Lipi,Apoorva Chakraborty,Apoorva Nanda,Pranjala Shukla

This work aims to address the historical development of the great Indian raga tradition, enhanced by computational approaches, and to use computational strategies to analyze aspects of contemporary Hindustani classical music (HCM). It is divided into two parts with Part 1 focusing on the history and aesthetics of HCM and Part 2 covering its computational aspects. The historical development of HCM in the ancient, medieval and modern periods; its terms and genre; and its Khayal gharanas are covered in Part 1. The subtopics include essential concepts such as raga, tala, shruti, thaat, gharana, khayal, dhrupad, thumri, tappa, etc. Part 2 covers the state-of-the-art in computational musicology, raga analysis and song analysis using statistics. The subtopics include statistical modeling, inter onset interval, note duration analysis, pitch movement between the notes, rate of change of pitch (pitch velocity) and probabilistic analysis of musical notes. The author concludes the work with reflecting on the lives of a few renowned musicians and musicologists with an account of hilarious moments taken from their lives to excite the reader to know more about HCM. This book would be useful for musicians, musicologists, researchers in music history, aesthetics, computational musicology, and advanced undergraduate and postgraduate students of music and musicology.

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141

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Sanctum Books

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ISBN 10

8194783003

ISBN 13

9788194783008

Sentiment Analysis of Music using Statistics and Machine Learning

By: Aakash Mukherjee,Soubhik Chakraborty

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Sentiment Analysis of Music using Statistics and Machine Learning

By: Aakash Mukherjee,Soubhik Chakraborty

Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.

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ISBN 10

8195293174

ISBN 13

9788195293179

Computational Musicology in Hindustani Music

By: Soubhik Chakraborty,Guerino Mazzola,Swarima Tewari,Moujhuri Patra

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Computational Musicology in Hindustani Music

By: Soubhik Chakraborty,Guerino Mazzola,Swarima Tewari,Moujhuri Patra

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.

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116

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Springer

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ISBN 10

3319114727

ISBN 13

9783319114729

Signal Analysis of Hindustani Classical Music

By: Asoke Kumar Datta,Sandeep Singh Solanki,Ranjan Sengupta,Soubhik Chakraborty,Kartik Mahto,Anirban Patranabis

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Signal Analysis of Hindustani Classical Music

By: Asoke Kumar Datta,Sandeep Singh Solanki,Ranjan Sengupta,Soubhik Chakraborty,Kartik Mahto,Anirban Patranabis

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.

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259

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Springer

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ISBN 10

9811039593

ISBN 13

9789811039591

Statistical Analysis of Folk Songs of Jharkhand

By: Shivani Tiwari,Soubhik Chakraborty

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Statistical Analysis of Folk Songs of Jharkhand

By: Shivani Tiwari,Soubhik Chakraborty

Folk songs play a very significant role in Indian classical music as the root of Indian classical music is the Indian folk music itself. Different states have different folk songs. This work deals with the statistical analysis of the folk songs of Jharkhand. Each song's analysis concerns with verifying whether the probabilities of notes in the song are fixed throughout the song or are the note probabilities varying. This tells us whether the probability distribution followed by the notes is multinomial or quasi multinomial respectively. Statistical parameterization method is used to quantify melody and rhythm. The presence of rhythm and melody is also analyzed by the Inter Onset Interval (IOI) and note duration graphs. The book should be found useful by music researchers and students of music and musicology, ethnomusicologists and music enthusiasts.

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Sanctum Books

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ISBN 10

8195293166

ISBN 13

9788195293162

Musical Cryptography. Empirical Analysis of Algorithms

By: Shailly Ranjan,Soubhik Chakraborty,Sandip Dutta

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Musical Cryptography. Empirical Analysis of Algorithms

By: Shailly Ranjan,Soubhik Chakraborty,Sandip Dutta

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.

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GRIN Verlag

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ISBN 10

3346268888

ISBN 13

9783346268884

Musical information retrieval. Signal Analysis and Feature Extraction using Python

By: M. Sai Chaitanya,Soubhik Chakraborty

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Musical information retrieval. Signal Analysis and Feature Extraction using Python

By: M. Sai Chaitanya,Soubhik Chakraborty

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.

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GRIN Verlag

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ISBN 10

3346455246

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9783346455246

Sentiment Analysis of Music using Statistics and Machine Learning

By: Aakash Mukherjee,Soubhik Chakraborty

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Sentiment Analysis of Music using Statistics and Machine Learning

By: Aakash Mukherjee,Soubhik Chakraborty

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Sanctum Books

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ISBN 10

8195293174

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9788195293179

Statistical Analysis of Folk Songs of Jharkhand

By: Shivani Tiwari,Soubhik Chakraborty

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Statistical Analysis of Folk Songs of Jharkhand

By: Shivani Tiwari,Soubhik Chakraborty

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8195293166

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9788195293162

Hindustani Classical Music

A Historical and Computational Study

By: Soubhik Chakraborty,Swarima Tewari,Arshi Rahman,Maria Jamal,Apra Lipi,Apoorva Chakraborty,Apoorva Nanda,Pranjala Shukla

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Hindustani Classical Music

A Historical and Computational Study

By: Soubhik Chakraborty,Swarima Tewari,Arshi Rahman,Maria Jamal,Apra Lipi,Apoorva Chakraborty,Apoorva Nanda,Pranjala Shukla

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141

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Sanctum Books

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ISBN 10

8194783003

ISBN 13

9788194783008

Computational Musicology in Hindustani Music

By: Soubhik Chakraborty,Guerino Mazzola,Swarima Tewari,Moujhuri Patra

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Computational Musicology in Hindustani Music

By: Soubhik Chakraborty,Guerino Mazzola,Swarima Tewari,Moujhuri Patra

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116

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Springer

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ISBN 10

3319114727

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9783319114729

Outlier Analysis. A Study of Different Techniques

By: Priyabrata Mishra,Soubhik Chakraborty

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Outlier Analysis. A Study of Different Techniques

By: Priyabrata Mishra,Soubhik Chakraborty

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.

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GRIN Verlag

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ISBN 10

3346702456

ISBN 13

9783346702456

Signal Analysis of Hindustani Classical Music

By: Asoke Kumar Datta,Sandeep Singh Solanki,Ranjan Sengupta,Soubhik Chakraborty,Kartik Mahto,Anirban Patranabis

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Signal Analysis of Hindustani Classical Music

By: Asoke Kumar Datta,Sandeep Singh Solanki,Ranjan Sengupta,Soubhik Chakraborty,Kartik Mahto,Anirban Patranabis

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259

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Springer

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ISBN 10

9811039593

ISBN 13

9789811039591

Probabilistic Analysis of a Random Determinant

By: Nikita Saha,Soubhik Chakraborty

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Probabilistic Analysis of a Random Determinant

By: Nikita Saha,Soubhik Chakraborty

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.

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GRIN Verlag

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ISBN 10

3668965080

ISBN 13

9783668965089

Objective Classification of Hindustani Ragas

By: Poonam Priyadarshini,Soubhik Chakraborty

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Objective Classification of Hindustani Ragas

By: Poonam Priyadarshini,Soubhik Chakraborty

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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151

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GRIN Verlag

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ISBN 10

3668948321

ISBN 13

9783668948327

Book's by Soubhik Chakraborty

Hindustani Classical Music

Hindustani Classical Music

Sentiment Analysis of Music using Statistics and Machine Learning

Sentiment Analysis of Music using Statistics and Machine Learning

Computational Musicology in Hindustani Music

Computational Musicology in Hindustani Music

Signal Analysis of Hindustani Classical Music

Signal Analysis of Hindustani Classical Music

Statistical Analysis of Folk Songs of Jharkhand

Statistical Analysis of Folk Songs of Jharkhand

Musical Cryptography. Empirical Analysis of Algorithms

Musical Cryptography. Empirical Analysis of Algorithms

Musical information retrieval. Signal Analysis and Feature Extraction using Python

Musical information retrieval. Signal Analysis and Feature Extraction using Python

Sentiment Analysis of Music using Statistics and Machine Learning

Sentiment Analysis of Music using Statistics and Machine Learning

Statistical Analysis of Folk Songs of Jharkhand

Statistical Analysis of Folk Songs of Jharkhand

Hindustani Classical Music

Hindustani Classical Music

Computational Musicology in Hindustani Music

Computational Musicology in Hindustani Music

Outlier Analysis. A Study of Different Techniques

Outlier Analysis. A Study of Different Techniques

Signal Analysis of Hindustani Classical Music

Signal Analysis of Hindustani Classical Music

Probabilistic Analysis of a Random Determinant

Probabilistic Analysis of a Random Determinant

Objective Classification of Hindustani Ragas

Objective Classification of Hindustani Ragas

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