7 papers · 1 filter
Automatic Detection and Analysis of Singing Mistakes for Music Pedagogy
Sumit Kumar, Suraj Jaiswal, Parampreet Singh +1
The advancement of machine learning in audio analysis has opened new possibilities for technology-enhanced music education. This paper introduces a framework for automatic singing…
Learning to Discover: A Generalized Framework for Raga Identification without Forgetting
Parampreet Singh, Somya Kumar, Chaitanya Shailendra Nitawe +1
Raga identification in Indian Art Music (IAM) remains challenging due to the presence of numerous rarely performed Ragas that are not represented in available training datasets. Tr…
Learning from Limited Labels: Transductive Graph Label Propagation for Indian Music Analysis
Parampreet Singh, Akshay Raina, Sayeedul Islam Sheikh +1
Supervised machine learning frameworks rely on extensive labeled datasets for robust performance on real-world tasks. However, there is a lack of large annotated datasets in audio…
Improving Active Learning for Melody Estimation by Disentangling Uncertainties
Aayush Jaiswal, Parampreet Singh, Vipul Arora
Estimating the fundamental frequency, or melody, is a core task in Music Information Retrieval (MIR). Various studies have explored signal processing, machine learning, and deep-le…
Recognizing Ornaments in Vocal Indian Art Music with Active Annotation
Sumit Kumar, Parampreet Singh, Vipul Arora
Ornamentations, embellishments, or microtonal inflections are essential to melodic expression across many musical traditions, adding depth, nuance, and emotional impact to performa…
Meta-learning-based percussion transcription and identification from low-resource audio
Rahul Bapusaheb Kodag, Vipul Arora
This study introduces a meta-learning-based approach for low-resource Tabla Stroke Transcription (TST) and identification in Hindustani classical music. Using Model-Ag…