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.
Table of Contents
- Preface
- Introduction
- Background and motivation
- Unique characteristic of Indian music
- Characteristic of Music
- Characteristic of Ragas
- Features for classification
- Objective of the book
- Outline of the book
- Literature
- Survey
- Study of Artist Behaviour from Raga Performance
- Introduction
- Mel frequency cepstral co-efficients
- Statistical parametrization
- Analysis and Results
- Music classification
- Confusion matrix
- Summary
- Comparison Between Restful and Restless Ragas Using Basic Statistical Features
- Introduction
- Research methodology
- Experimental results
- Pitch transition
- Analysis of transitory and non-transitory frequency movements between Notes
- Summary
- Comparison Between Restful and Restless Ragas Using Advanced Statistical Features
- Introduction
- Research Methodology
- Experimental Result
- Modeling the Pilu and Todi Raga performance statistically
- Single Exponential Smoothing for raga Todi gives a bad fit
- Single Exponential Smoothing for raga Pilu gives a comparatively better fit.
- Results and Discussion
- Summary
- Statistical Modeling of Raga Todi Performance
- Introduction
- Indian Classical Music
- Musical features of raga Todi
- Double exponential smoothing
- Model equation
- Forecasts
- Experimental Result
- Discussion
- Summary
- Statistical Study of Music Emotion
- Introduction
- Research methodology
- Statistical parameterization
- Experimental Results
- Summary
- Concluding Remarks
Objectives and Key Themes
This book aims to identify key features of musical signals that allow for the objective classification of Hindustani ragas. The research explores methods for classifying ragas based on various parameters and statistical modeling techniques. The study contributes to the scientific understanding of Indian classical music, specifically Hindustani music, through quantitative analysis.
- Objective classification of Hindustani ragas using signal processing techniques.
- Analysis of artist-specific variations in raga performance.
- Statistical comparison of "restful" and "restless" ragas.
- Statistical modeling of raga performance using exponential smoothing methods.
- Exploration of the relationship between musical features and perceived emotion.
Chapter Summaries
Introduction: This chapter provides background information on the study of Hindustani ragas and the challenges associated with their objective classification. It highlights the unique characteristics of Indian music, specifically its melodic structure (ragas), and discusses the need for objective classification methods in the context of large digital music libraries. The chapter defines the book's objective – to find important features of the music signal for raga classification – and outlines the book's structure.
Study of Artist Behaviour from Raga Performance: This chapter investigates the use of Mel Frequency Cepstral Coefficients (MFCCs) and statistical parametrization to analyze the performance of Hindustani ragas by different artists. The analysis aims to determine whether artists belonging to the same Gharana (musical school) exhibit similar performance characteristics. The results are analyzed using Andrew plots to visualize similarities and differences in raga interpretations. This chapter establishes a methodology for using quantitative analysis to study subtle variations in raga performances.
Comparison Between Restful and Restless Ragas Using Basic Statistical Features: This chapter compares "restful" and "restless" ragas using basic statistical features and inter-onset intervals. The research methodology is explained, and experimental results are presented. The focus is on identifying statistically significant differences in pitch transitions and frequency movements between the notes of these two types of ragas. The study demonstrates that quantitative analysis can reveal distinctions in the perceived emotional impact of different ragas.
Comparison Between Restful and Restless Ragas Using Advanced Statistical Features: This chapter extends the previous chapter’s analysis by employing advanced statistical features to compare restful and restless ragas. The methodology involves statistical modeling of raga performances, specifically using single and double exponential smoothing techniques for different ragas (Pilu, Todi, and Bhairavi). The chapter discusses the results and their implications for understanding the differences between these two types of ragas, highlighting the efficacy of different statistical models for representing various musical characteristics.
Statistical Modeling of Raga Todi Performance: This chapter focuses on the statistical modeling of the raga Todi, a raga considered restful in nature. The chapter provides background on Indian Classical Music and the musical features of raga Todi. It uses double exponential smoothing to model the raga's performance, presenting the model equation, forecasts, and experimental results. The discussion section analyzes the model's accuracy and its insights into the temporal structure of the raga. The chapter demonstrates the application of time-series analysis techniques to understanding the characteristic patterns of a specific raga.
Statistical Study of Music Emotion: This chapter explores the relationship between statistical parameters extracted from musical signals and the perceived emotion in Hindustani music. It details the research methodology employed, including the statistical parameterization used, and presents the experimental results. The chapter aims to provide quantitative evidence linking specific musical features to the listener's perception of emotional content within the music, suggesting a potential path towards automatically classifying music based on its emotional impact.
Keywords
Hindustani Ragas, Indian Classical Music, Mel Frequency Cepstral Coefficients (MFCCs), Statistical Modeling, Exponential Smoothing, Raga Classification, Music Emotion, Artist Performance, Pitch Transition, Inter-onset Interval, Gharana.
Frequently Asked Questions about "A Comprehensive Study of Hindustani Ragas Through Statistical Modeling"
What is the main topic of this book?
This book focuses on the objective classification of Hindustani ragas (melodic frameworks in Indian classical music) using signal processing and statistical modeling techniques. It aims to identify key features of musical signals that allow for the objective classification of these ragas.
What methods are used in this study?
The book employs various methods, including Mel Frequency Cepstral Coefficients (MFCCs) for signal analysis, statistical parametrization, exponential smoothing (single and double), and other advanced statistical techniques to model and compare raga performances. The research also involves analyzing pitch transitions and inter-onset intervals.
What are the key themes explored?
Key themes include objective raga classification, analysis of artist-specific variations in raga performance, statistical comparison of "restful" and "restless" ragas, statistical modeling of raga performance, and the exploration of the relationship between musical features and perceived emotion.
What types of ragas are compared?
The study specifically compares "restful" and "restless" ragas, using both basic and advanced statistical features. Examples of ragas analyzed include Todi and Pilu.
What are the objectives of the study?
The main objective is to develop and apply objective methods for classifying Hindustani ragas based on their musical characteristics. This involves identifying distinguishing features that allow for automatic classification and understanding the statistical properties of raga performances.
What are the key findings or conclusions?
The book presents findings on the use of statistical methods to differentiate between ragas, including the effectiveness of different statistical models for capturing the nuances of raga performances. It also explores the connection between musical features and perceived emotions in the music.
What is the structure of the book?
The book is structured into several chapters. It begins with an introduction, followed by literature review, a survey of existing work, and then delves into specific studies on artist behavior, comparison of restful and restless ragas (using both basic and advanced statistical features), statistical modeling of specific ragas (like Todi), and a study of music emotion. The book concludes with concluding remarks.
What are the key keywords associated with this research?
Key terms include Hindustani Ragas, Indian Classical Music, Mel Frequency Cepstral Coefficients (MFCCs), Statistical Modeling, Exponential Smoothing, Raga Classification, Music Emotion, Artist Performance, Pitch Transition, Inter-onset Interval, and Gharana (musical school).
For whom is this book intended?
This book is intended for researchers, academics, and students interested in Indian classical music, signal processing, statistical modeling, and music information retrieval. The quantitative approach and detailed analysis make it valuable for those seeking a scientific understanding of Hindustani ragas.
Where can I find more information about this book?
Further details about the specific methodologies, results, and conclusions are provided within the full text of the book. (Note: This FAQ only summarizes the provided preview.)
- Arbeit zitieren
- Poonam Priyadarshini (Autor:in), Soubhik Chakraborty (Autor:in), 2019, Objective Classification of Hindustani Ragas, München, GRIN Verlag, https://www.grin.com/document/469399
