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1
Aswale, Swati, Dr Prabhat Chandra Shrivastava, Dr Ratnesh Ranjan, and Seema Shende. "Indian Classical Music Recognition using Deep Convolution Neural Network." International Journal of Electrical and Electronics Research 12, no. 1 (2024): 73–82. http://dx.doi.org/10.37391/ijeer.120112.
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A divine approach to communicate feelings about the world occurs through music. There is a huge variety in the language of music. One of the principal variables of Indian social legacy is classical music. Hindustani and Carnatic are the two primary subgenres of Indian classical music. Models have been trained and taught to distinguish between Carnatic and Hindustani songs. This paper presents Indian classical music recognition based on multiple acoustic features (MAF) consisting of various statistical, spectral, and time domain features. The MAF provides the changes in intonation, timbre, prosody and pitch of the musical speech due to different ragas. The lightweight DCNN is used to improve the representation of the raga sound and to provide higher order abstract level features. The overall performance of the raga type is estimated using various performance metrics, including accuracy, precision, recall and F1-score. The proposed DCNN achieves an accuracy, precision, recall, and F1-score of 89.38%, 0.89, 0.89, and 0.89, respectively, for eight raga classifications. The extensive experimentation on eight classical ragas has shown a noteworthy improvement over the traditional state of art.
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Aswale, Swati, Dr Prabhat Chandra Shrivastava, Dr Ratnesh Ranjan, and Seema Shende. "Indian Classical Music Recognition using Deep Convolution Neural Network." International Journal of Electrical and Electronics Research 12, no. 1 (2024): 73–82. http://dx.doi.org/10.37391/10.37391/ijeer.120112.
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A divine approach to communicate feelings about the world occurs through music. There is a huge variety in the language of music. One of the principal variables of Indian social legacy is classical music. Hindustani and Carnatic are the two primary subgenres of Indian classical music. Models have been trained and taught to distinguish between Carnatic and Hindustani songs. This paper presents Indian classical music recognition based on multiple acoustic features (MAF) consisting of various statistical, spectral, and time domain features. The MAF provides the changes in intonation, timbre, prosody and pitch of the musical speech due to different ragas. The lightweight DCNN is used to improve the representation of the raga sound and to provide higher order abstract level features. The overall performance of the raga type is estimated using various performance metrics, including accuracy, precision, recall and F1-score. The proposed DCNN achieves an accuracy, precision, recall, and F1-score of 89.38%, 0.89, 0.89, and 0.89, respectively, for eight raga classifications. The extensive experimentation on eight classical ragas has shown a noteworthy improvement over the traditional state of art.
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Anagha A. Bidkar, Yogesh H. Dandawate, Rajkumar S. Deshpande. "North Indian Classical Instrumental Raga Music: Multifractal Parameters Analysis and Raga Recognition System." Journal of Information Systems Engineering and Management 10, no. 29s (2025): 962–74. https://doi.org/10.52783/jisem.v10i29s.4611.
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Introduction: The foundation of Indian classical music is the raga. Ancient music literature describes raga as a collection of particular arrangement of musical notes, that turns into soothing music. According to basic music theory, the raga segments have fractal properties. In fractal theory, the scale of the music note (signal) can be altered while maintaining its shapeObjectives: This enhances musical quality with improved raga note. In the proposed work, Codebook of Feature (CoF) model is used to recognize 12 Indian classical ragas. The application considered is north Indian classical instrumental raga music. The multifractal parameter analysis of musical segments is done, based on fractal theory.Methods: The proposed work recognizes raga without note detection, hence reducing the complexity of the raga recognition system. The training and testing datasets considered are 60 % – 40 % and 90 % – 10 % respectively.Results: The accuracy obtained is 98.94 % and 99.01 % respectively. The accuracy calculated based on F1 – score for the mentioned datasets is 98.93 % and 99.06 % respectively.Conclusions: The proposed system is also compared with the recognition of raga using previous work on the same dataset that was implemented with variants of Mel Frequency Cepstral Coefficients (MFCC) features and the ensemble bagged tree as a classifier, which gives 96.32% accuracy. The proposed system's accuracy has increased by 3% compared to MFCC features.
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Pragyan Paramita Rout, Rageshree swain, and Sanhita Padhi. "Effect of synchronized sound waves in the form of Indian Classical Ragas on Phytochemical analysis of Chamaecostus cuspidatus (Nees & Mart.) C. Specht & D. W. Stev." International Journal of Frontiers in Biology and Pharmacy Research 3, no. 1 (2022): 018–29. http://dx.doi.org/10.53294/ijfbpr.2022.3.1.0049.
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Synchronized sound waves in the form of Indian classical ragas have a remarkable impact on the living beings. According to various studies, Indian Classical music has been confirmed to encourage plant growth positively and it is observed that the sounds from metal-rock, rock, rap, pop, and monotonous sounds have a negative impact on plant growth. The present research work was aimed at finding the impact and effect of the synchronized sound waves and their frequencies in different strings and closed-pipe Indian classical instrumental music displayed through various Ragas, viz: Raga- Kedar (flute), Raga- Kedar (santoor), Raga-Rageshree (sitar), Raga-Bhairavi (flute), Raga- Shree (Sarangi), Raga- Milan kiTodi (Sarod), Raga- Ramkali (Sitar) on phytochemical analysis in the leaves of Insulin (Chamaecostus cuspidatus). The standard deviation values in all of the pure solvents indicates that the data were spread over a wider range of values, which further showed that the treated plants have higher concentration phytochemicals when compared to that of the untreated samples. The total phenol content was found to be 207.66±0.33 mg/GAE per gram extract and 113.33±3.33 mg/GAE per gram extract in case of treated and untreated plant samples of Chamaecostus cuspidatus respectively. Similarly, the total flavonoid content was found to be 37.66±0.33 mg QE/g extract and 26.66±0.33 mg QE/g extract in case of treated and untreated plant samples respectively and the total tannin content was found to be 843±1.99 mg TAE/g extract and 503±0.57 mg TAE/g extract in case of treated and untreated plant samples respectively.
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Rajan, Rajeev, and Sreejith Sivan. "Raga Recognition in Indian Carnatic Music Using Convolutional Neural Networks." WSEAS TRANSACTIONS ON ACOUSTICS AND MUSIC 9 (May 7, 2022): 5–10. http://dx.doi.org/10.37394/232019.2022.9.2.
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A vital aspect of Indian Classical music (ICM) is raga, which serves as a melodic framework for compositions and improvisations for both traditions of classical music. In this work, we propose a CNN-based sliding window analysis on mel-spectrogram and modgdgram for raga recognition in Carnatic music. The impor- tant contribution of the work is that the pro- posed method neither requires pitch extraction nor metadata for the estimation of raga. CNN learns the representation of raga from the pat- terns in the melspectrogram/ modgdgram dur- ing training through a sliding-window analysis. We train and test the network on sliced-mel- spectrogram/modgdgram of the original audio while the nal inference is performed on the au- dio as a whole. The performance is evaluated on 15 ragas from the CompMusic dataset. Multi- stream fusion has also been implemented to identify the potential of two feature representations. Multi-stream architecture shows promise in the proposed scheme for raga recognition.
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Roy, Samarjit, Sudipta Chakrabarty, and Debashis De. "Time-Based Raga Recommendation and Information Retrieval of Musical Patterns in Indian Classical Music Using Neural Networks." IAES International Journal of Artificial Intelligence (IJ-AI) 6, no. 1 (2017): 33. http://dx.doi.org/10.11591/ijai.v6.i1.pp33-48.
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In Indian Classical Music (ICM) perspective, Raga is formed from the different and correct combination of notes. If it is observed the history of Indian Classical Raga in ICM, the playing or serving each of the ragas has some unique sessions. The procedure is to suggest the classifications of playing a raga has been attempted to display by explaining unique musical features and pattern matching. This contribution has been represented how music structures can be advanced through a more conceptual demonstration and consent to unambiguously describe process of computational modeling of Musicology which signify the challenge on complete musical composition from the elementary vocal objects of ICM usage using Neural Networks. In Neural network the samples of various ragas have been taken as input and classify them according to the times of the performance. Over 90% accuracy level has achieved using entire Confusion Matrices and Error Histogram performance evaluation technique.
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Samarjit, Roy, Chakrabarty Sudipta, and De Debashis. "Time-Based Raga Recommendation and Information Retrieval of Musical Patterns in Indian Classical Music Using Neural Networks." IAES International Journal of Artificial Intelligence (IJ-AI) 6, no. 1 (2017): 33–48. https://doi.org/10.5281/zenodo.4108231.
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In Indian Classical Music (ICM) perspective, Raga is formed from the different and correct combination of notes. If it is observed the history of Indian Classical Raga in ICM, the playing or serving each of the ragas has some unique sessions. The procedure is to suggest the classifications of playing a raga has been attempted to display by explaining unique musical features and pattern matching. This contribution has been represented how music structures can be advanced through a more conceptual demonstration and consent to unambiguously describe process of computational modeling of Musicology which signify the challenge on complete musical composition from the elementary vocal objects of ICM usage using Neural Networks. In Neural network the samples of various ragas have been taken as input and classify them according to the times of the performance. Over 90% accuracy level has achieved using entire Confusion Matrices and Error Histogram performance evaluation technique.
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Kari, Yamini Krishna. "Evaluation of music through C programming-Challenges and Limitations." Naad Nartan Journal of Dance and Music 12, no. 1 (2024): 47–53. https://doi.org/10.5281/zenodo.11030914.
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<em>The development stages of music have drastically changed with technology in various areas like recording, sound generation </em><em>software, and studio equipment, etc. Among all other technological aspects, basic programming languages like C, C++, and </em><em>C# play a vital role in the advancement of music. This research paper mainly focuses on generating swarasthanas and the </em><em>sounds of swarasthanas using C Programming Language commands. It proves that C programming language can be used to </em><em>generate 12 notes of Indian music and Swarasthanas of 72 Melakarta ragas of Carnatic classical music. Using code editors </em><em>like VS Code and a compatible compiler for C, these different musical sounds can be created. This process illustrates writing </em><em>a C program for Mohana Raga Geetham in Carnatic Classical Music, and the Indian National Anthem. This research work </em><em>also explains how to write a similar C program that displays the Swarasthanas of the chosen raga from the programmed 72 </em><em>Melakartha Ragas. Challenges and limitations of the output would be discussed in the conclusion of the paper.</em> <em>Keywords: C Programming, Mohana Raga, National Anthem, 72 Melakartha Ragas, Swarasthanas.</em>
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Pal, Tanmoy. "An Analysis of Indian Music Aesthetics with Particular Reference to Hindustani Classical Music." Praxis International Journal of Social Science and Literature 6, no. 5 (2023): 1–9. https://doi.org/10.51879/PIJSSL/060501.
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<em>Indian classical music is thought to arouse the emotions (Rasas) within. The aesthetics of music have assisted various researchers in discovering its practical use for a healthier living. Both Hindustani ragas have the ability to evoke the rasas. Raga treatment is thought to be useful in alleviating tension, relaxing the mind, and regulating blood flow. Raga treatment has numerous health benefits, as our ancient texts have long stated. This article attempts to demonstrate how the emotions in music have been effectively demonstrated to be a beneficial tool in the treatment of many psychological, neurological, and emotional problems.</em>
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Jani, Pooja A., and Shweta Jejurkar. "Contribution of Kramik Pustak Malika of Chatur Pandit in the field of Indian Music and its Relevance." HARIDRA 2, no. 07 (2021): 62–70. http://dx.doi.org/10.54903/haridra.v2i07.7773.
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Indian Classical Music is the best gift of Indian culture to the world. Indian Classical Music is of two types – उत्तर हिन्दुस्तानी संगीत पद्धति एवं दक्षिण हिन्दुस्तानी संगीत पद्धति. The roots of Indian Music are found in Vedas. Sanskrit is the ancient language and we found it in the Vedas. Many treatises related to music systems are also found in Sanskrit Language. To learn music properly, every learner has to go through two paths – 1. Theoretical music (Ancient treatises) 2. Practical Music (which follows Guru Shishya tradition). Pandit Bhatkhande has given wonderful and helpful notation system to Indian Classical Music. With the help of it he has collected many Bandish from different people and made a large collection. This collection is known as Kramik Pustak Malika. (Parts 1 -6). All these six parts are having theory of 150 ragas divided Thata-wise, with introductory chapter on the general theory of music, besides a short description of every Raga, followed by Svar-vistar. They contain about 1000 traditional compositions including Pandit Bhatkhande’s own compositions which are about 300 in notation. To know the Raga deeply, one can refer the same book and can get many Bandish, Svar-vistar, information about Ragas, their descriptions given in Sanskrit treatises, Thata (थाट), Tala, etc. Therefore, Kramik Pustak Malika of Chatur Pandit is the treasure of Indian Music.
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Kalyani C. Waghmare, Et al. "PMFCC Features for Music Classification Using the Modified KNN Algorithm." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 4191–95. http://dx.doi.org/10.17762/ijritcc.v11i9.9793.
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From ancient period Music is a integral part of human life. People prefered to listen Music while relaxing. All over the world nowadays music is used as supporting medication for healing mental illness and many other diseases. The origin of Indian Music is Indian Classical Raga, having a melodious combination of Rhythm and notes. There are various users like music-composers, e-learners, music therapists are frequently retrieving Indian classical Raga based music. The vast retrieval of Raga based music made it necessary to classify Indian music on Raga. This paper proposes an a new algorithm to classify an Indian Music using Raga information which further will be useful for song recommendation, personalizing collection, and musicologists for various purpose.
 In this paper, the combined Pitch and MFCC based PMFCC features are extracted and processed by Modified K Nearest Neighbor algorithm. The performance of PMFCC and Pitch Class Distribution features is compared using traditional machine learning classification algorithms and Modified Variant K Nearest Neighbor (MVKNN). The PMFCC features outperformed with the Modified KNN algorithm. The accuracy of PMFCC features with Modified KNN algorithm is found 96.11% for our Our dataset and 93.65% for Compmusic standard dataset.
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Mukherjee, Roan. "Impact of Music Intervention (Listening to Indian Classical Music) on Mental Wellbeing during COVID-19 Pandemic." Jurnal Litbang Edusaintech 2, no. 2 (2021): 63–78. http://dx.doi.org/10.51402/jle.v2i2.19.
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Background: Reports show that mental wellbeing may be negatively affected by the COVID-19 pandemic. The ragas of Indian classical music are believed to have therapeutic effects. This study was done to investigate the impact of an Indian raga on mental wellbeing during the COVID-19 pandemic. Materials and Methods: It was a one-group before-after design study. A total of 45 adult subjects of Kolkata, recruited online, using convenience sampling during the lockdown, underwent a pre-test via Google forms using Warwick-Edinburg Mental Wellbeing Scale (WEMWBS) to evaluate mental wellbeing before the administration of music intervention. After two weeks of music intervention, that consisted of passively listening to raga Hamsadhwani, a post-test using the same scale and the same medium was done. Results: The results showed that the post-test mean of the total score 51.1 (SD = 3.9) of WEMWBS was significantly (p< 0.001) higher than the pre-test mean of the total score 30.9 (SD = 4.6). The same trend was reflected by the mean difference pertaining to all of the components of WEMWBS. Conclusion: It was concluded that raga Hamsadhwani may be effective in improving mental wellbeing in a pandemic situation. There is a need to do more work by improvising the research design employed in the present study. This will help to interpret more accurately and more meaningfully the effects of Indian raga music on mental wellbeing.
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Chakraborty, Soubhik, and Swarima Tewari. "A Statistical Analysis of Bhairav-The first morning Raga." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 2 (2005): 371–86. http://dx.doi.org/10.24297/ijct.v4i2b1.3225.
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A raga, in Indian classical music, is a melodic structure with fixed notes and a set of rules characterizing a particular mood conveyed by performance. Bhairav is the first raga of the morning. The present paper gives a statistical analysis of this raga structure. Â
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Waghmare, Kalyani C., and Balwant A. Sonkamble. "Raga Identification Techniques for Classifying Indian Classical Music: A Survey." International Journal of Signal Processing Systems 5, no. 4 (2017): 130–35. http://dx.doi.org/10.18178/ijsps.5.4.130-135.
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Rout, Pragyan P., Rageshree Swain, and Sanhita Padhi. "Effect of Synchronized Sound Waves in the form of Indian Classical Ragaas on Phytohormonal Analysis of Medicinal Plant Species." Scholars Academic Journal of Biosciences 10, no. 3 (2022): 26–32. http://dx.doi.org/10.36347/sajb.2022.v10i03.001.
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Music, based on the synchronized sound waves has a tremendous impact on the living beings. Different frequencies of synchronized sound are now-a-days used in therapy (being popularly called as music therapy). However, the impact of music on physical and physiological processes of the living beings has been acknowledged since ages. Rhythmic and comforting music has an influence on behavior of all living organisms such as humans, plants and animals. According to various studies, Indian Classical music has been confirmed to encourage plant growth positively and it is observed to dominate the other important genres of music such as metal-rock, rock, rap, pop, and monotonous sounds. The present research work was aimed at finding the exclusive impact and effect of the synchronized sound waves and their frequencies in different strings and closed-pipe Indian classical instrumental music displayed through various Ragaas, viz: Raga Kedar (flute), Raga Kedar (santoor), Raga-Rageshree (sitar), Raga-Bhairavi (flute), Raga- Shree (Sarangi), Raga- Milan ki Todi (Sarod), Raga- Ramkali (Sitar) on phytohormonal analysis in Insulin (Chamaecostus cuspidatus) and stevia (Stevia rebaudiana). Enhanced phytohormonal levels were observed in the plant species treated with different Indian classical Ragaas. In both Chamaecostus cuspidatus and Stevia rebaudiana the total concentration of GA3 was found to be 37.33mg/ml and 96.77mg/ml in treated plants respectively. Similarly in Chamaecostus cuspidatus and Stevia rebaudiana the concentration of IAA at 222nm was found to be 2.33 and 7.71mg/ml and at 280nm was found to be 8.45mg/ml and 41.90mg/ml in treated plants respectively.
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Pudaruth, Santosh Kumar. "A Reflection on the Aesthetics of Indian Music, With Special Reference to Hindustani Raga-Sangita." SAGE Open 6, no. 4 (2016): 215824401667451. http://dx.doi.org/10.1177/2158244016674512.
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Like in any other heteronomous art-forms, the practitioners of Indian music and dance ( Bharatiya Sangita) aim at expressing emotions and creating the aesthetic or the “beautiful.” Indian thinkers and musicologists have gone a step further in declaring that Indian classical music ( Raga-Sangita) is the most appropriate means for attaining aesthetic experience and delight, and the most suitable pathway, if not, downright, short-cut, toward self-realization or realization of the Ultimate Reality or Truth. Thus, aesthetics and spirituality make up the very woof and warp of the Indian arts, in general, and Raga-Sangita, in particular. Raga-Sangita is, thus, considered a spiritual exercise ( nada sadhana) to attain salvation ( moksha) through sound. This conceptual article reflects upon and sheds light on the Theory of Rasa, as propounded in Indian Aesthetics, and attempts to make an assessment of it in relation to Hindustani Raga-Sangita. Through this theory, the author examines and explains the different causes leading to an aesthetic experience, referred to as “out-of-this-world” ( alaukika). In doing so, he also brings to light the possible pitfalls which both the performer and the listener should avoid.
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Srikrithi Santhanam, Srinithi Santhanam, A. Advika, and M. Azhagiri. "Melody Magic: Generating Indian Classical Music According to Mood using Natural Language Processing." international journal of engineering technology and management sciences 7, no. 6 (2023): 194–99. http://dx.doi.org/10.46647/ijetms.2023.v07i06.030.
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Indian classical music is a rich and intricate tradition that weaves together melodies, rhythms, and intricate improvisations, reflecting a profound connection between spirituality and artistic expression. This paper explores the development and implementation of an innovative raga based musical chatbot that utilizes NLP techniques to generate Indian Classical music tailored to specific moods or emotions. This is done by employing sentiment analysis and deep learning algorithms. The system can interpret textual descriptions and facial expression of emotions and translate them into melodious compositions. Beyond artistic expression, our system also leverages the therapeutic potential of music, allowing users to customize their listening experience for stress reduction and potential health benefits. This research bridges tradition and technology, offering a unique approach to raga therapy.
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Kalyani, C. Waghmare, and A. Sonkamble Balwant. "Machine Learning Algorithms for Indian Music Classification Based on Raga Framework." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 9, no. 11 (2020): 130–34. https://doi.org/10.35940/ijitee.K7724.0991120.
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The supervised and unsupervised learning methods in Machine Learning are successfully applied to solve various real time problems in different domains. The Indian Music has a base of Raga structure. The Raga is melodious framework for composition and improvisation. The identification and indexing of Raga for Indian Music data will improve efficiency and accuracy of retrieval being expected by e-learners, composers and classical music listeners. The identification of Raga in Indian Music is very difficult task for naïve user. The application of machine learning algorithms will definitely be best key idea. The paper demonstrates K-means and Agglomerative clustering methods from unsupervised learning nonetheless K Nearest Neighbor, Decision Tree and Support Vector Machine and Naïve Bayes classifiers are implemented from supervised learning. The partition of 70:30 is done for training data and testing data. Pitch Class Distribution features are extracted by identifying Pitch for every frame in an audio signal using Autocorrelation method. The comparison of above algorithms is done and observed supervised learning methods outperformed.
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Paschalidou, Stella, and Ioanna Miliaresi. "Multimodal Deep Learning Architecture for Hindustani Raga Classification." Sensors & Transducers 261, no. 2 (2023): 86. https://doi.org/10.5281/zenodo.10696544.
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In this paper, our key aspect is the design of a deep learning architecture for the classification of Hindustani (classical North Indian music) ragas (music modes). In an attempt to address this task, we propose a modular deep learning architecture designed to process data from two modalities, comprising audio recordings and metadata. Our bipolar classifier utilizes convolutional and feed forward neural networks and incorporates spectral information of audio data and metadata descriptors tailored to the peculiar melodic characteristics of Hindustani music. In specific, audio recordings as well as manually annotated and automatically extracted metadata were utilized for audio samples of both Hindustani improvisations and compositions available in the Saraga open dataset of Indian art music. Experiments are conducted on two Hindustani ragas, namely Yaman and Bhairavi. Results indicate that the integration of multimodal data increases the classification accuracy of the classifier in comparison to simply using audio features. Additionally, for the specific task of raga classification the use of the swaragram feature, which is customized for Hindustani music, outperforms the effectiveness of audio features that are commonly used in Eurocentric music genres.
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Sujatashamkuwar, Dr, V. Ashokan, Yogita Shrivas, Pratibha Baghel, and S. Sujata. "Effect of Classical Music on Fetus: A Review." Journal of Ayurvedic and Herbal Medicine 8, no. 2 (2022): 119–24. http://dx.doi.org/10.31254/jahm.2022.8211.
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Even before birth, music may have a significant impact on your child's development. Music stimulates all aspects of a child's growth when they are exposed to it. And doing so at a young age may assist guarantee that your child grows up to be healthy. In several psychological conditions, music therapy is known to be effective, but not much research has been done to ascertain the effect of classical Indian music on psychiatric disorders. The ascendant is the antenatal musical practice. With reference to evidence-based study, the paper supports 5 primary objectives: music therapeutic modulation of pre- and perinatal stress, anxiety, and depression; mental and physical birth planning related to music, including cognitive change, emotional regulation, physical exercise, maintenance of relaxation and discomfort, and social inclusion; music-related bonding and self-efficacy; prenatal sound enhancement. Traditional therapeutic tools include Raga Chikitsa, Vedic chanting, Garbha Sanskara (Learning in the Womb), Time theory of ragas (combining ancient Ayurvedic notions) and Cakra activation (music and breathing approach using ragas). Outcomes in clinical are studied to see how they impact biological, physiological, psychological, chronobiological, as well as spiritual factors.
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Sahastrabuddhe, Bhagyashree. "THE USE OF CLASSICAL RAGA YEMEN IN CINE MUSIC - AN IDEA." International Journal of Research -GRANTHAALAYAH 3, no. 1SE (2015): 1–3. http://dx.doi.org/10.29121/granthaalayah.v3.i1se.2015.3439.
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Hindustani music is based on raga. The definition of raga has been given by different scholars with their own method, but the meaning of all has been referenced by "sound" in particular, the voice of the Varna Varnishtha: Ranjjjan, Chittananas: Raga: The so-called "Buddha". Therefore, it can be said that the soul of Indian music resides only in the raga composition which creates the pigmentation with the tone and color. The railing structure stands on the building box. On the rough side, it is assumed that in the construction of an octave, the original 12 vowels are the same in the construction of the rhyme, in preparing the structure of a building. The foundation work is done.
 हिन्दुस्तानी संगीत राग पर आधारित है। राग की परिभाषा अलग-अलग विद्वान¨ं ने अपनी-अपनी पद्धति से दी है परन्तु सबका आशय ”य¨ऽयं ध्वनिविषेषस्तु स्वर वर्ण विभूषितः रंजक¨जन चित्तानां सः रागः कथित¨ बुेधैः“ से ही संदर्भित रहा है। अतः यह कहा जा सकता है कि भारतीय संगीत की आत्मा स्वर, वर्ण से युक्त रंजकता पैैदा करने वाली राग रचना में ही बसती है। स्वर¨ं क¢ बिल्ंिडग बाॅक्स पर राग का ढाँचा खड़ा ह¨ता है। मोटे त©र पर ये माना गया है कि एक सप्तक क¢ मूल 12 स्वर सा रे रे ग ग म म प ध ध नि नि राग क¢ निर्माण में वही काम करते हैं ज¨ किसी बिल्डिंग क¢ ढाँचे क¨ तैयार करने में नींव का कार्य ह¨ता है।
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Gajjar, Kunjal, and Mukesh Patel. "Computational Musicology for Raga Analysis in Indian Classical Music: A Critical Review." International Journal of Computer Applications 172, no. 9 (2017): 42–47. http://dx.doi.org/10.5120/ijca2017915211.
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Bardekar, Ashish A. "Synthesis of Indian Classical Raga Darbari Structural Influence on Human Brain Waves." International Journal for Research in Applied Science and Engineering Technology 6, no. 3 (2018): 2666–71. http://dx.doi.org/10.22214/ijraset.2018.3593.
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Sinith, M. S., Shikha Tripathi, and K. V. V. Murthy. "Raga recognition using fibonacci series based pitch distribution in Indian Classical Music." Applied Acoustics 167 (October 2020): 107381. http://dx.doi.org/10.1016/j.apacoust.2020.107381.
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Chakraborty, Apoorva, and Soubhik Chakraborty. "The fifth music therapy session: Hindustani classical music and its therapeutic value." MOJ Biology and Medicine 8, no. 4 (2023): 177–78. http://dx.doi.org/10.15406/mojbm.2023.08.00206.
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We hereby present a brief report on the fifth and final music therapy session in connection with our ongoing research project titled Hindustani Raga Analysis Using Statistical Musicology with Therapeutic Applications for Stress Management sponsored by IDEAS: Technology Innovation Hub @ Indian Statistical Institute, Kolkata. Details of the first four music therapy sessions have been published and the interested reader is referred to Chakraborty S et al.1–4
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Dipti, Joshi, Pareek Jyoti, and Ambatkar Pushkar. "Comparative Study of Mfcc and Mel Spectrogram for Raga Classification Using CNN." Indian Journal of Science and Technology 16, no. 11 (2023): 816–22. https://doi.org/10.17485/IJST/v16i11.1809.
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Abstract <strong>Objectives:</strong> To perform a comparative study of the results of feature extraction done using two different methods, Mfcc and Mel spectrogram, and determine which method is more effective for implementing the CNN algorithm. <strong>Methods:</strong> This study uses the CNN model to classify ragas according to Indian classical music. Feature extraction, which is a major operation in the Music Information Retrieval (MIR) process, is done using Mfcc and Mel spectrogram methods. The major ragas chosen as subjects for feature extraction are Yaman, Bhairav, Bhairavi, Multani, and Dhanashree.<strong> Findings:</strong> After comparison and examination of results achieved from both techniques, we could conclude that the CNN model using the Mel spectrogram method outperforms the CNN model using Mfcc. <strong>Novelty:</strong> The majority of the research, we discovered was on Carnatic music. In contrast to earlier research, this research takes a novel approach by conducting experiments on a variety of Hindustani classical ragas which are different from other studies. Researchers interested in music as well as application users would benefit from this study. Our proposed feature extraction approach will be useful for initializing the CNN algorithm, which will help aspiring musicians recognize ragas and classify songs based on these ragas. <strong>Keywords:</strong> Raga identification; Music Information Retrieval; Feature extraction; Mfcc; Melspectrograms; CNN
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Kumaraswamy, Balachandra, and Poonacha P G. "Recognizing ragas of Carnatic genre using advanced intelligence: a classification system for Indian music." Data Technologies and Applications 54, no. 3 (2020): 383–405. http://dx.doi.org/10.1108/dta-04-2019-0055.
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PurposeIn general, Indian Classical Music (ICM) is classified into two: Carnatic and Hindustani. Even though, both the music formats have a similar foundation, the way of presentation is varied in many manners. The fundamental components of ICM are raga and taala. Taala basically represents the rhythmic patterns or beats (Dandawate et al., 2015; Kirthika and Chattamvelli, 2012). Raga is determined from the flow of swaras (notes), which is denoted as the wider terminology. The raga is defined based on some vital factors such as swaras, aarohana-avarohna and typical phrases. Technically, the fundamental frequency is swara, which is definite through duration. Moreover, there are many other problems for automatic raga recognition model. Thus, in this work, raga is recognized without utilizing explicit note series information and necessary to adopt an efficient classification model.Design/methodology/approachThis paper proposes an efficient raga identification system through which music of Carnatic genre can be effectively recognized. This paper also proposes an adaptive classifier based on NN in which the feature set is used for learning. The adaptive classifier exploits advanced metaheuristic-based learning algorithm to get the knowledge of the extracted feature set. Since the learning algorithm plays a crucial role in defining the precision of the raga recognition, this model prefers to use the GWO.FindingsThrough the performance analysis, it is witnessed that the accuracy of proposed model is 16.6% better than NN with LM, NN with GD and NN with FF respectively, 14.7% better than NN with PSO. Specificity measure of the proposed model is 19.6, 24.0, 13.5 and 17.5% superior to NN with LM, NN with GD, NN with FF and NN with PSO, respectively. NPV of the proposed model is 19.6, 24, 13.5 and 17.5% better than NN with LM, NN with GD, NN with FF and NN with PSO, respectively. Thus it has proven that the proposed model has provided the best result than other conventional classification methods.Originality/valueThis paper intends to propose an efficient raga identification system through which music of Carnatic genre can be effectively recognized. This paper also proposes an adaptive classifier based on NN.
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Vibhavari, Rajadnya, and Kalyani Joshi Dr. "Raga Classification Based on Novel Method of Pitch Co-Occurrence." International Journal of Recent Technology and Engineering (IJRTE) 11, no. 1 (2022): 23–27. https://doi.org/10.35940/ijrte.A6886.0511122.
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<strong>Abstract: </strong>Automatic identification of raga is a growing research area and has captured significant attention from movie making industry. It is the need of time to develop efficient tools for data mining the vast audio visual data on internet. In particular, to search for a specific raga. Applications of raga search are in musicological studies, similarity based search. Ascending and descending pattern of swaras is an important feature in the raga classification. Pitch tracks of swaras are obtained from raw audio recordings. This research has utilised the pattern developed due to co-occurrence of pitches of swaras for classification. This pattern gives a concise representation of the signal which contains time and frequency information of the raga. K Nearest Neighbour (KNN) has been used as the classifier.
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Blume, Gernot. "Blurred affinities: tracing the influence of North Indian classical music in Keith Jarrett's solo piano improvisations." Popular Music 22, no. 2 (2003): 117–42. http://dx.doi.org/10.1017/s0261143003003088.
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In the first forty years of his career, American pianist Keith Jarrett has established a reputation in multiple stylistic directions. Jarrett has typically incorporated influences as varied as bebop, country, rock, gospel, minimalism, baroque and classical styles into his often lengthy improvisations. Vital to his musical persona, but less obvious, is the influence North Indian classical music has had in shaping Jarrett's improvisatory strategies. Although he never formally studied Indian music, and although his instrument – the piano – is far removed from the conceptual backdrop of North Indian raga performance, Indian music was a central component in the artistic climate out of which his improvised solo recitals grew.A cultural climate of global influences was the backdrop to the development of Jarrett's solo concerts. Therein, perhaps, lies one key to understanding the spell that this music has cast on large and international audiences. With this format, Jarrett tapped into the ambiance of a particular historic moment, which combined a desire for change with the discovery of spiritual and musical traditions outside the Western world.In this paper I will demonstrate how explicit and implicit references to classical Indian principles of music making helped shape Jarrett's unique free solo concerts.
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Philips, Anna Amy. "Embracing indian and western classical music in the 21st century: Param Vir and Shankar Tucker." Musica paedagogia pilsnensis 1, no. 1 (2021): 73–80. http://dx.doi.org/10.24132/zcu.musica.2021.01.73-80.
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The first (published) mention of Indian classical music in Western discourse takes us to William Jones’ On the Musical Modes of the Hindus (1784), which ignited a scholarly interest for the Orient in the Western world. Since then, over the years, several researchers in music have been swept along and consumed by the currents of lost, found, translated, (mis-)inter - preted, transliterated and transformed literature on Indian classical music 2. This work delves neither into the labyrinth of the allusive character of Raga, nor the theory, transliteration, and treatises on Indian classical music. Instead, with supporting literature from many diligent scholars, it utilises all the extremely elaborate theories and explanations from the past to initiate a different sort of analysis in this field, one that explores musical material directly in compositions which incorporate both Indian and Western music, using socio-cultural, media studies theories and music analysis theories. The primary intent of this work is to comprehend the creation of a cultural third space brought about by the hybridisation of contemporary Western music and Indian classical music, taking two composers as case studies for this purpose: Param Vir and Shankar Tucker. The parameters of this study centre, in Vir’s case, on Indian classical- and 20 th century Western classical music theories; and, in Tucker’s case, the appropriation of Indian music, using contemporary media studies and popular music the- ories of a globalised world. Such an analysis is customised and therefore is to be considered as an observation of the current scenario within these two systems of music, within these parameters.
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Swati Shilaskar, Et al. "Thaat Classification Using Recurrent Neural Networks with Long Short-Term Memory and Support Vector Machine." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1377–88. http://dx.doi.org/10.17762/ijritcc.v11i10.8680.
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This research paper introduces a groundbreaking method for music classification, emphasizing thaats rather than the conventional raga-centric approach. A comprehensive range of audio features, including amplitude envelope, RMSE, STFT, spectral centroid, MFCC, spectral bandwidth, and zero-crossing rate, is meticulously used to capture thaats' distinct characteristics in Indian classical music. Importantly, the study predicts emotional responses linked with the identified thaats. The dataset encompasses a diverse collection of musical compositions, each representing unique thaats. Three classifier models - RNN-LSTM, SVM, and HMM - undergo thorough training and testing to evaluate their classification performance. Initial findings showcase promising accuracies, with the RNN-LSTM model achieving 85% and SVM performing at 78%. These results highlight the effectiveness of this innovative approach in accurately categorizing music based on thaats and predicting associated emotional responses, providing a fresh perspective on music analysis in Indian classical music.
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Meddegoda, Chinthaka Prageeth. "Hindustani Classical Music in Sri Lanka: A Dominating Minority Music or an Imposed Musical Ideology?" ASIAN-EUROPEAN MUSIC RESEARCH JOURNAL 6 (December 4, 2020): 41–50. http://dx.doi.org/10.30819/aemr.6-3.
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In Sri Lanka, the various groups of Tamils are jointly the largest minority group who migrated from different places of South India and in different time periods. South Indian music is widely appreciated and learnt by both the Sinhala including by large parts of the Tamil minority spread over Sri Lanka. Although a number of Sinhala people prefer and practice North Indian music geographically, and probably culturally, they are much closer to South India than to North India. Some historical sources report that Sinhalese are descendants of North Indians who are believed to be Aryans who migrated from Persia to the Northern part of India in the 13th century and later. Therefore, some scholarly authorities believe that the Sinhalese ‘naturally’ prefer North Indian music as they also continue the suggested Aryan heritage. Nevertheless, some other sources reveal that the North Indian music was spread in Sri Lanka during the British rule with the coming of the Parsi Theatre (Bombay theatre), which largely promoted Hindustani raga-based compositions. This paper explores selected literature and opinions of some interviewees and discusses what could be the reasons for preferences of North Indian music by the Sinhalese. The interviewees were chosen according to their professional profile and willingness to participate in this research. As a result, this paper will offer insights through analysing various opinions and statements made by a number of interviewees. The research also considered some theories which may relate to the case whether Hindustani classical music is due to these reasons a dominating minority culture or a rather self-imposed musical ideology. The latter would establish an aesthetic hierarchy, which is not reflected in the cultural reality of Sri Lanka. This is a new research scrutinizing a long-term situation of performing arts education in this country taking mainly interviews as a departing point.
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Sharma, Sunil, Charu Bansal, Umesh Shukla, and Jain Trupti. "Assessment of the Effect of Raga Therapy & Nisha Amalaki Churna on Prehypertension - A clinical study." International Journal of Ayurvedic Medicine 12, no. 4 (2021): 948–53. http://dx.doi.org/10.47552/ijam.v12i4.2162.
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Background: Prehypertension is classified as elevated blood pressure above normal by American medical classification. JNC 7 suggested systolic between 120 to 139 mmHg or diastolic 80 to 89 mmHg should be consider as Pre-hypertension. Oxidative stress develops due to stress and anxiety is recognized as main risk factor for initiation of hypertension. The Nada Yoga (sound based yoga) practices has been reported to decreases stress and anxiety. Nisha Amalaki Churna the combination of Amalaki (Indian gooseberry) and Haridra (turmeric) powder also reported to effectively reduces oxidative stress. Aim - To assess the combined effect of Indian Classical Raga Ahirbhairav and Hindol along with Nisha Amalaki Churna on Prehypertension. Material and method- It was clinical study. Total 48 patients selected by purposive sample technique and then divided into 2 groups (n = 24 each) randomly. Assessment was done by criteria of pre hypertension given by JNC 7. Result - In present study group A (Raga Ahirbhairav, Raga Hindol and Nisha Amalki Churna) patients the mean score of Systolic B.P. had decreased from 135.50 to 120.76 (Mean difference 14.74) with extremely significance (p <0.0001) compare to group B (only Nisha Amalki Churna orally) and mean score of Diastolic B.P. had decreased from 88.61 to 79.706 (Mean difference 8.904) with extremely significant (p <0.0001) compare to group B. Relief in mild headache 31.94% (p<0.01), relief in Anxiety 52.67% (p<0.0001) and relief on stress was reported 34.56% (p<0.0001) in Group A were reported, compare to Group B. Conclusion- result of study indicating that Raga therapy with Nisha Amalaki Churna had potential in the management of pre hypertension.
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KSharma, Akhilesh, Avinash Panwar, and Prasun Chakrabarti. "Analytical Approach on Indian Classical Raga Measures by Feature Extraction with EM and Naive Bayes." International Journal of Computer Applications 107, no. 6 (2014): 41–46. http://dx.doi.org/10.5120/18759-0035.
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Nafde, Dr Mrs Tanuja. "Relevance of Music in Vedic Traditions and Contemporary Context." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 4954–58. http://dx.doi.org/10.22214/ijraset.2021.36036.
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Indian classical music has a very long-accumulated heritage of centuries. The origin of Indian music can be traced back to nearly two thousand years ago. It is undisputedly believed that the sage Narada introduced the art of music to the Earth, also it is said that the sound that pervades the whole universe, i.e. Nadabrahma, itself represents divinity. Scientifically structured Indian music owes its origin to the Samaveda. The Veda scriptures describe all the seven notes of the raga karaharpriya in descending order, which is a favorite research topic theory and treatise writers to explore, how the core sound ‘Om’ gave rise to the various notes. The first evidential reference to music dates back to 500 BC by Panini and the first reference to musical theory dates back to 400 BC found in Rikpratisakhya. Bharata’s Natya Shastra dating 4th Century AD contains several chapters on music. This is the first known work that clearly elaborated the octave of its structured characteristics for various applications. There is an eternal statement about the history of Indian Music, that "classical Indian music is derived from the Vedas". Although no one can say that this statement is false, it is deceptively simplistic, when discussing the Relevance of Music in Vedic Traditions and contemporary context.
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Chakraborty, Soubhik, Rayalla Ranganayakulu, Shivee Chauhan, Sandeep Singh Solanki, and Kartik Mahto. "Given a raga recording, can we scientifically verify which school of Vadi-Samvadi selection is supported by the artist?" INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 2 (2013): 288–300. http://dx.doi.org/10.24297/ijct.v4i2a2.3174.
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The notes which play the most important and second most important roles in expressing a raga are called Vadi and Samvadi swars respectively in (North) Indian Classical music. Like Bageshree, Bhairavi, Shankara, Hamir and Kalingra, Rageshree is another controversial raga so far as the choice of Vadi-Samvadi selection is concerned where there are two different opinions. Rather than ruling out any school of thought, the paper aims at identifying scientifically the particular school supported by a given recording. Thus the problem investigated here is one of classification in nature. In the present work, a two minute vocal recording of raga Rageshree is subjected to a careful statistical analysis. Our analysis is broken into three phases: first one minute, middle one minute and last one minute. Under a multinomial model set up holding appreciably in the first two phases, only one opinion is found acceptable. An interesting musical cocktail is proposed embedding several ideas like melodic property of notes, note combinations and pitch movements between notes, using some weighted combination of psychological and statistical stability of notes along with watching carefully the sudden shoot of one or more notes whenever there is enough evidence that multinomial model has broken down..Â
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Janaki Devi M and Baiju Krishnan. "Amit Chaudhuri: The Writer’s Writer." International Journal of Applied and Scientific Research 3, no. 5 (2025): 341–54. https://doi.org/10.59890/ijasr.v3i5.28.
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This study aims to examine Amit Chaudhuri’s dual identity as both a writer and a trained Hindustani classical musician, exploring how his musical sensibilities shape his literary style, thematic preoccupations, and narrative rhythm. Amit Chaudhuri is an acclaimed Indian novelist and essayist whose work often resists conventional narrative structures. His literary output—marked by lyrical prose, digressive form, and an acute attention to the everyday—is influenced by his background as a vocalist trained in Indian classical music. Understanding the intersection of these two artistic identities reveals his contribution to postcolonial and modernist literature. The analysis reveals that Chaudhuri’s prose mirrors the improvisational and meditative structures of classical raga. His narratives prioritise mood and tone over plot progression, with deliberate attention to rhythm, repetition, and silence—techniques derived from his musical training. Themes such as transience, nostalgia, and aesthetic contemplation recur consistently across his work. Chaudhuri’s musicality is not only thematic but also structural; his fiction constructs meaning through tone, cadence, and lyrical detours. His work challenges conventional literary form by foregrounding aesthetic experience over narrative urgency, aligning him with modernist experimentation while remaining rooted in Indian artistic traditions. By synthesising literary and musical practices, Amit Chaudhuri emerges as a unique figure in contemporary literature. His dual identity enriches his writing with a distinct voice that defies genre boundaries and expands the possibilities of literary expression. This dual sensibility positions him not only as a postcolonial writer but also as a transdisciplinary artist of notable innovation
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Dr., Padmini Shreedhar. "Ṭhāya – A Pre-Modern Era Musical Form – With Special Reference To Its Adaptation Into The Classical Dance Tradition Of Karnāṭaka". Smṛti - A Bi-Annual Peer Reviewed Journal on Fine & Performing Arts 4, № 1 (2024): 1–11. https://doi.org/10.5281/zenodo.13765685.
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The south Indian classical music forms of the pre-modern era were based on four forms namely Gīta, Ālāpa, Ṭhāya, and Prabandha. “The earliest textual mention of the four melodic forms in one sequence is available in Ramamatya’s Svaramēļa Kalanidhi of 1550 A.D.”. (Seeta 46: 1979). All genres of classical music were classified under these four forms exclusively. Later Venkatamakhi, the musicologist of the 16th century called the four musical forms as the ‘Caturadaṇḍi’ or four pillars of south Indian music. The ṭhāya as a composition with a specific structure was used for perfecting a raga. Tulaja’s Saṅgīta Sārāmruta illustrates the usage of ṭhāya under various ragas. The manuscript collection of TSSML demonstrates the illustrative formats of ṭhāya with ‘Nam tom’ syllables. It seems to have been performed as a nṛtta composition as per historical records in the courts of the Nayaks of Thanjavur along with the above mentioned three forms. Parallelly, the Karnāṭaka Gurus adapted the ṭhāya into the dance performance format and modified it into a nṛtya composition by adding a lyrical structure. As the melodious rendition of ṭhāya created a devotional ambience for a temple dance offering, it was included in the ālaya repertory. The ṭhāyas have traversed in the oral tradition to the 20th century in the Kolar sampradāya of Karnāṭaka classical dance heritage. A few examples are found in the 19th century manuscripts of its preceptor Yajmann Kolar Kittanna. This paper discusses the structure of the ṭhāya, its historicity, form and content, relevance, and purpose of its special inclusivity in the dance repertoire. The discussion is based on the references from both the textual and the oral practising traditions. This is a phenomenological study with an interpretative approach, including exploratory and historical research.
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Barthakur, Spandan Kumar, Parismita Sarma, and Gaurav Narayan Baruah. "Acoustic Feature Identification to Recognize Rag Present in Borgit." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7 (2023): 182–93. http://dx.doi.org/10.17762/ijritcc.v11i7.7844.
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In the world of Indian classical music, raga recognition is a crucial undertaking. Due to its particular sound qualities, the traditional wind instrument known as the borgit presents special difficulties for automatic raga recognition. In this research, we investigate the use of auditory feature identification methods to create a reliable raga recognition system for Borgit performances. Each of the Borgits, the devotional song of Assam is enriched with rag and each rag has unique melodious tune. This paper has carried out few experiments on the audio samples of rags and a few Borgits sung with those rugs. In this manuscript three mostly used rags and a few Borgits with these rags are considered for the experiment. Acoustic features considred here are FFT (Fast Fourier Transform), ZCR (Zero Crossing Rates), Mean and Standard deviation of pitch contour and RMS(Root Mean Square). After evaluation and analysis it is seen that FFT and ZCR are two noteworthy acoustic features that helps to identify the rag present in Borgits. At last K-means clustering was applied on the FFT and ZCR values of the Borgits and were able to find correct grouping according to rags present there. This research validates FFT and ZCR as most precise acoustic parameters for rag identification in Borgit. Here researchers had observed roles of Standard deviation of pitch contour and RMS values of the audio samples in rag identification.
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Kulkarni, GururajB, and Dhanaraj Chittapur. "Effects of long term Indian classical Raga Therapy in reduction of Blood Pressure among chronic hypertensive patients." APIK Journal of Internal Medicine 5, no. 3 (2017): 10. http://dx.doi.org/10.4103/2666-1802.260084.
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Samarpita Chatterjee Mukherjee. "Musical Analysis, Beauty and Spirituality of Selected Bandishes (Compositions) of Ustad Latafat Hussain Khan." International Journal of Social, Political and Economic Research 7, no. 1 (2020): 26–35. http://dx.doi.org/10.46291/ijospervol7iss1pp26-35.
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The musical structure, as well as the lyrics of the bandish (composition), have an integral relationship with the performance of the composition by a vocalist or musician. Although Classical Music is primarily a performing art, it incorporates literary and poetic contents, which makes it more impressive, intriguing, and engaging to one's heart. The genre of classical music has been enriched by the creative work of several composers of Indian Classical Vocal music. Ustad Latafat Hussain Khan was one of the stalwart musicians of the Agra style of Indian Classical music. He was not only an eminent vocalist but also created many bandishes under the pseudonym ‘Premdas.’ This present writing presents the actual meaning/semantics of the bandish, inner meaning or philosophical essence and the spiritual/religious perspective portrayed by the composer in three of his selected Khayal bandishes. By presenting the notation of these bandish, in the concerned raga, the embedded melody format, beautification of the taal and laya (rhythm and tempo) with the help of Swara (voice sound/ tone) and lyrics (Bol) by the composer has been analyzed. The reflection of characteristics of Agra style in the bandish has discussed. For the study, personal interviews of eminent musicians and existing pieces of concerned literature had been consulted. It may be said that the analysis of these bandishes of Ustad Latafat Hussain Khan made it evident that they bear the signature of his skillful ability and his uniqueness as a vibrant composer.
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Pragya, Pyasi Sanjoy Bandopadhyay. "Do the YouTube views count reflects the seniority and acceptance of Indian classical musicians within fraternity or the vice-versa?" Naad Nartan Journal of Dance and Music 10, no. 1 (2022): 17–24. https://doi.org/10.5281/zenodo.7054839.
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YouTube is a highly dominating music distribution platform. Previous studies indicate the relations between YouTube music videos, the role of the algorithm, musical creativity, user-generated content, and user engagement. The current investigation aims to understand the bi-directional relationships between the YouTube views, selected aspects of music, and the musicians. The study obtained 257 sample videos of 87 musicians of different categories. The researchers used YouTube filters to collect sample videos, and the obtained data were statistically analyzed using pivot tables and the Chi-square test. The results show that the seniority and popularity of musicians in the ICM fraternity are not decisive factors for high YouTube views. When the research output shows an equal distribution of Instrumental and Vocal Music performances, the Male-Female ratio in the high-viewed YT presence is not equal. The study also successfully established different levels of presence of Classical, Neo-Classical, and other music renderings by the Hindustani Raga musicians. This study reveals the necessity for identifying the functional components leading to high YouTube views.
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Pyasi, Pragya, and Sanjoy Bandopadhyay. "Do the YouTube Views Count Reflects the Seniority and Acceptance of Indian Classical Musicians within Fraternity or the Vice-Versa?" Naad-Nartan Journal of Dance & Music (ISSN: 2349-4654) 10, no. 1 (2022): 17–24. https://doi.org/10.5281/zenodo.7056304.
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YouTube is a highly dominating music distribution platform. Previous studies indicate the relations between YouTube music videos, the role of the algorithm, musical creativity, user-generated content, and user engagement. The current investigation aims to understand the bi-directional relationships between the YouTube views, selected aspects of music, and the musicians. The study obtained 257 sample videos of 87 musicians of different categories. The researchers used YouTube filters to collect sample videos, and the obtained data were statistically analyzed using pivot tables and the Chi-square test. The results show that the seniority and popularity of musicians in the ICM fraternity are not decisive factors for high YouTube views. When the research output shows an equal distribution of Instrumental and Vocal Music performances, the Male-Female ratio in the high-viewed YT presence is not equal. The study also successfully established different levels of presence of Classical, Neo-Classical, and other music renderings by the Hindustani Raga musicians. This study reveals the necessity for identifying the functional components leading to high YouTube views.
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Pennanen, Risto. "Lost in scales: Balkan folk music research and the ottoman legacy." Muzikologija, no. 8 (2008): 127–47. http://dx.doi.org/10.2298/muz0808127p.
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Balkan folk music researchers have articulated various views on what they have considered Oriental or Turkish musical legacy. The discourses the article analyses are nationalism, Orientalism, Occidentalism and Balkanism. Scholars have handled the awkward Ottoman issue in several manners: They have represented 'Oriental' musical characteristics as domestic, claimed that Ottoman Turks merely imitated Arab and Persian culture, and viewed Indian classical raga scales as sources for Oriental scales in the Balkans. In addition, some scholars have viewed the 'Oriental' characteristics as stemming from ancient Greece. The treatment of the Seg?h family of Ottoman makams in theories and analyses reveals several features of folk music research in the Balkans, the most important of which are the use of Western concepts and the exclusive dependence on printed sources. The strategies for handling the Orient within have meandered between Occidentalism and Orientalism, creating an ambiguity which is called Balkanism.
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Kulkarni, Apeksha, Jibi Varghese, Abhilasha Lagad, and Manna Mathew. "Potential implications of Ayurvedic treatment along with Marma chikitsa and Indian classical music therapy in Ardhavabhedak i.e (Migraine without aura)." International Journal of Ayurvedic Medicine 16, no. 1 (2025): 274–78. https://doi.org/10.47552/ijam.v16i1.5329.
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The brain is the most complex organ of the human body. It is the crown jewel of the body as it performs various essential functions. Globally, headache disorders affect approximately 40% of the population, nearly 3.1 billion people in 2021(1). It is more common in females as compared to males. Headache disorders ranked third (after stroke and dementia) in accounting for overall neurological disease burden as measured by age-standardized disability-adjusted life years (DALYs) in 2019. It comes with a constellation of things that it impacts person’s activities of daily living and affect their ability to do things that they love the most. Migraine without aura is a recurrent and debilitating disorder having pulsatile, unilateral moderate to severe headache lasting from 2-72 hours. Associated symptoms include nausea, vomiting, photosensitivity and phonosensitivity. In Ayurveda it is correlated with one of the Shirorogas i.e Ardhavabhedak. According to Acharya Charaka it is Vata-Kaphaja and according to Acharya Sushrut it is Tridoshaja vyadhi. In this case study, a male patient of middle age suffering from chronic severe migraine was treated with the Ayurveda medications and panchakarma resulting in significant relief. An additional Marma chikitsa and Indian classical music i.e Raga Mohanam therapy was also given. The integrative treatment modality has shown significant relief in reducing the episodes and intensity of pain of Migraine (Ardhavabhedak).
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Snigdhatanu, Banerjee. "To trace the Gharana maestros, ever been in Princely Tripura." Pratidhwani the Echo (A Peer-Reviewed International Journal of Humanities & Social Science) [UGC Approved, Journal No: 48666] VIII, no. I (2019): 140–51. https://doi.org/10.5281/zenodo.8094718.
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This article or research paper covers the patronization and practice of Hindustani Classical Music of Princely Tripura. Information about Music maestros from renowned Gharanas who were associated with music training and performances therein, are clearly described.
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Pillai, Anjana Muralidharan, and Dr Darshan Jitendra Dave. "Evaluation of the effect of Indian classical music on the blood sugar level of Type-2 Diabetes Mellitus patients." Music and Medicine 10, no. 4 (2018): 175. http://dx.doi.org/10.47513/mmd.v10i4.615.
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Background: Type-2 Diabetes Mellitus, being a major health care problem, needs to be managed holistically. Stress has been identified as an important etiological factor and music therapy helps to alleviate it; a study has been conducted to assess the effect of Indian Classical Music on blood sugar level of Type-2 Diabetes Mellitus patients vis-à-vis non-diabetic individuals. Methodology: An interventional study was conducted on Type-2 Diabetes Mellitus patients attending Medicine outpatient department (OPD) receiving oral antidiabetic agents with same dosage regimen for the past two months. Similarly non-diabetic healthy volunteers were recruited from the general population after taking their informed consent. Random blood sugar (RBS) was estimated without and with exposure to Raga Bageshree for 30 min in test and control group subjects respectively. Result: On applying relevant statistical tests to the data generated, significant reduction in blood sugar was found in individual groups i.e both control and test groups of non-diabetic as well as diabetic subjects. But, there was no statistical difference in the change in blood sugar level in test groups versus control groups in diabetic as well as non-diabetic patients. (p=0.789, p=0.379). Conclusion: No statistically significant improvement in blood sugar level was observed in diabetic as well as non-diabetic test subjects because of music. Considering small sample size, single exposure to music as limitations and also looking at it as the first study of its kind, long term studies involving a larger sample size and chronic exposure to music are recommended for definite conclusion.
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Manjunath, Bajantri, Tavargi Tavargi, and Jeyaram Srinivasan. "Impact of Indian classical raga on symptom profile and functionality in patients with schizophrenia enrolled in rehabilitation center: integrative perspectives from a case series." Bulletin of Integrative Psychiatry 94, no. 3 (2022): 36–41. http://dx.doi.org/10.36219/bpi.2022.3.03.
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Komangoda, Lahiru Gimhana. "Vinay Mishra and the Artistry of the Harmonium." ASIAN-EUROPEAN MUSIC RESEARCH JOURNAL 8 (December 9, 2021): 39–46. http://dx.doi.org/10.30819/aemr.8-5.
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Vinay Mishra is an accomplished Indian solo and accompanying harmonium player born and brought up in Benaras and currently residing in Delhi serving as a faculty member of the Department of Music, Faculty of Music and Fine Arts, University of Delhi. The rigorous training of both vocal and instrumental music under veteran Hindustani Music virtuosos, the academic and scholarly scope built up till the degree of PhD in Music, the realizations, and understandings on music must have conspicuously made an impact of his practice and artistry as a harmonium player. Harmonium was originated in the west and adopted by Indian musicians in the colonial era which was brought up to the present day through many artistic, cultural and political controversies, and obstacles. This work focuses on discovering the insights of the harmonium art of Vinay Mishra. Hence, his academic background, musical training, musical career, his playing style as a soloist, general techniques and techniques of accompaniment, sense of machinery, perspectives on raga Taal, and thoroughly the tuning methods were studied in-depth through personal conversations and literature resources where it was observed that modern Hindustani harmonium artists favor a typical natural tuning method over the 12 equal temperaments of the common keyboard instruments. According to him, the stable sound of the harmonium was the reason to be vocal music- friendly in classical and light vocal music accompaniment which was only interrupted by the equal temperament earlier and was later overcome by the artists and harmonium makers. The idea was also raised that apart from gaining the basic command of an instrument, a Hindustani instrumentalist may learn and practice all other aspects of Hindustani music from the teachers of other forms too. Vinay Mishra’s thoughts of machinery, musical forms, compositions, applying Hindustani vocal, and plucking string instrumental ornamentations on the Harmonium were also reviewed.
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Dr Priyanka Sharma. "National Education Policy (2020) and Music." Knowledgeable Research: A Multidisciplinary Journal 1, no. 2 (2022): 42–46. http://dx.doi.org/10.57067/5d362s78.
Full textAbstract:
The National Education Policy 2020 is an attempt to give a national direction to Indian education and adapt it to modern technological, social, and economic changes. Music has been given an important role in this policy, which is extremely important to enrich the level of education and help in the development of students. Music has been considered an important source of psychological and educational benefits. The presence of music in education boosts the morale of students, improves their physical and mental health, and develops their thinking abilities. Through music, students develop sensitivity, dedication, and tolerance, which prepares them to succeed in every walk of life. Music is a skill that provides students with national thinking, new skills, and the ability to face unique problems. Music education develops various skills, such as collaboration, teamwork, problem solving, and innovation. This teaches students the importance of self-reference and self-study, which enhances their independence and sensitivity. Music education enhances social and cultural support. Through music, students get a chance to study and understand various cultural streams such as Indian music, classical music, folk music, singing, playing, raga, taal, and history of music etc. Furthermore, through music, students receive messages of various social and moral values, such as cooperation, equality, harmony, and collectivism. Thus, the National Education Policy has seen music as an important tool, which helps students in the overall development of their personality. Furthermore, through music, rich and unique experiences are provided to the students, which takes them into a deeper dialogue with music and sets them on the path to success in every walk of life. The National Education Policy 2020 has also included music in higher education at a support level. This has promoted music education not only at the primary and secondary levels, but music studies have also been considered important within higher education. This will give students an opportunity to study and gain more expertise in the subject of music. By including music as this important aspect of education, the National Education Policy 2020 has re-established the importance of music in the Indian society. This will allow students to have more exposure to and interest in music, thereby enabling them to reap the benefits of music through their personal and social development. By enhancing the role of music, the National Education Policy 2020 has provided students with a We have endeavored to provide excellent and enriching education, which will lead them towards meaning and prosperity in their lives. With this, an important step has been taken to understand and encourage the important role of music in the society.