In this paper, the predominant instrument recognition in polyphonic music is addressed
using timbral descriptors in three frameworks-Gaussian mixture model (GMM), deep neural …

Identification of multiple predominant instruments in polyphonic music is addressed using
convolutional neural networks (CNN) through Mel-spectrogram, modgd-gram, and its fusion …

Modified group delay functions are beginning to gain significance in the literature for formant
estimation, speaker recognition and speech recognition. In particular, group delay functions …

Group delay processing of audio signals has been extensively studied in the last decade. In
this paper, tonic estimation in Turkish makam music is addressed using modified group …

Poems, which communicate through rhythm and its apparent meaning have a vital role in
any literary. Meter, a set of well defined rules gives rhythm to the poetry. In this paper, a …

Spike estimation from calcium (Ca 2+) fluorescence signals is a fundamental and
challenging problem in neuroscience. Several models and algorithms have been proposed …

Automatic music genre classification based on distance metric learning (DML) is proposed
in this paper. Three types of timbral descriptors, namely, mel-frequency cepstral coefficient …

In this paper, predominant instrument recognition in polyphonic music is addressed using
convolutional recurrent neural networks (CRNN) through Mel-spectrogram, modgdgram …

Modified group delay based algorithms for estimation of melodic pitch sequences from
heterphonic/polyphonic music are discussed in this paper. Two different variants of the …

The block diagram of the proposed system is shown in Figure 1. The experiment is
conducted in four phases. In the first phase, a baseline system with MFCC features are used …