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Parsing natural acoustic scenes using computational methodologies poses many challenges. Given the rich and complex nature of the acoustic environment, data mismatch between train and test conditions is a major hurdle in data-driven audio processing systems. In contrast, the brain exhibits a remarkable ability at segmenting acoustic scenes with relative ease. When tackling challenging listening conditions...
Neurophysiological studies of sound encoding at the level of auditory cortex paint a picture of an intricate filterbank that encodes detailed spectral and temporal modulations in the sensory input. Furthermore, these filters exhibit adaptive qualities called neural plasticity that shape their tuning parameters in line with behavioral goals of interest. In this work, we explore qualitative principles...
In this paper we use a Non-negative Matrix Factorization (NMF) based approach to analyze the strokes of the mridangam, a South Indian hand drum, in terms of the normal modes of the instrument. Using NMF, a dictionary of spectral basis vectors are first created for each of the modes of the mridangam. The composition of the strokes are then studied by projecting them along the direction of the modes...
This work addresses the task of tonic pitch identification in Indian classical music. The drone or the tambura establishes the tonic in Indian classical music. A cepstrum based pitch extraction technique is proposed to identify the tuning of the tambura. We show that by identifying the musical note Sadja in the lower octave of a performance, the pitch of the tonic can be identified accurately. We...
In this work, we propose a novel application of the group delay function - to identify the tonic pitch in Carnatic music (one of the main sub genres of Indian classical music). Tonic pitch is the reference note chosen by a performer in Carnatic music. Automatic identification of the tonic pitch is essential in Carnatic music in order to perform data driven computational melodic analysis. Group delay...
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