Harmonizing Heritage: A Review of Advances in Indian Music Genre Classification

Abstract

The classification of Indian music genres represents a fascinating intersection of cultural richness and technological innovation. This review paper meticulously traces the evolutionary journey of music genre classification methodologies within the intricate domain of Indian music. Spanning from the foundational research in the early 2000s to the latest advancements in supervised, unsupervised, and deep learning approaches, we highlight seminal studies and their pivotal contributions. Our analysis encompasses the challenges and opportunities inherent in cross-cultural genre classification, fine-grained categorization, multimodal approaches, real-time classification, and resilience to noise and variability. Additionally, we explore novel deep learning architectures, genre evolution analysis, multilingual classification, and the critical role of open-access datasets. By synthesizing past achievements and elucidating future research directions and gaps, this paper serves as a beacon for further exploration, fostering interdisciplinary collaborations, and advancing our understanding and appreciation of the rich musical heritage of India. Through a critical lens, we identify significant research gaps and future directions, including the need for fine-grained genre classification, robustness against noise and variability, and the exploration of multimodal approaches. By offering insights into the complexities of classifying Indian music genres and outlining a roadmap for future research, this paper aims to stimulate further investigations, foster interdisciplinary collaborations, and facilitate the development of more accurate and culturally sensitive classification systems. Ultimately, our goal is to enrich the understanding and appreciation of Indian music’s profound cultural heritage through the lens of genre classification, paving the way for innovative applications in music recommendation, education, and digital archiving.