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@article{164678,
        author = {Shital Mantayya Durgam and Sumit Sunil Nandanwar and Yashayah Tirupati Boram and Naresh Gulab Jadhav},
        title = {MUSIC NOTE GENERATION USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {2067-2070},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164678},
        abstract = {The intersection of music and artificial intelligence (AI) has sparked innovative approaches to music generation, leveraging the power of machine learning (ML) algorithms. This abstract delves into the burgeoning field of music generation using ML techniques, presenting an overview of methodologies, challenges, and future directions.
Music generation with ML involves the utilization of algorithms to analyze patterns, structures, and styles inherent in musical compositions. From classical to contemporary genres, ML models can learn from existing musical datasets to generate novel compositions that mimic the characteristics of the training data. Techniques such as recurrent neural networks (RNNs), generative adversarial networks (GANs), and transformer models have been prominent in this domain.
},
        keywords = {},
        month = {},
        }