On an Ethical Use of Neural Networks: A Case Study on a North Indian Raga (original) (raw)
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IAES International Journal of Artificial Intelligence (IJ-AI), 2017
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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Because of its non-representational nature, music has always had familiarity with computational and algorithmic methodologies for automatic composition and performance. Today, AI and computer technology are transforming systems of automatic music production from passive means within musical creative processes into ever more autonomous active collaborators of human musicians. This raises a large number of interrelated questions both about the theoretical problems of artificial musical creativity and about its ethical consequences. Considering two of the most urgent ethical problems of Musical AI (music job replacement and machine musical authorship), we show in this essay the strict dependence of every form of acknowledgment of a moral and legal status to systems of automatic music production from the theoretical account of musical creativity by turns implicitly or explicitly adopted, arguing, on the basis of pragmatic reasons, for the necessity and the desirability of this acknowledgment.
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Introductory Studies on Raga Multi-track Music Generation of Indian classical music using AI
Zenodo (CERN European Organization for Nuclear Research), 2023
Recently, there has been an exponential expansion in research focusing on AI-based music generation. Our indepth analysis of the arXiv dataset revealed a growing number of publications on this subject: over 273 AI music papers in the past two years, with 102 explicitly tackling AI music generation. However, one area that seems underrepresented is Indian traditional music. This study presents the application of artificial intelligence (AI) in creating Indian classical music, focusing on Raga-based music generation. We outline the two-stage music creation process, including the creative and technical aspects, and explore how AI can be integrated into these stages. We trained the models using the LSTM (Long Short-term Memory network) and Transformer models on the Dunya dataset, which includes almost 250 ragas played across 12 instruments. Further, the study proposes a new Raga Multi-Track Music Model (RMMM) model to generate multi-layered Raga-based music with enhanced authenticity and emotional resonance. Despite potential challenges, this research opens an exciting journey in AI-generated Indian classical music.