A pairwise approach to simultaneous onset/offset detection for singing voice using correntropy

Abstract

In this paper, we propose a novel method to search for precise locations of paired note onset and offset in a singing voice signal. In comparison with the existing onset detection algorithms, our approach differs in two key respects. First, we employ Correntropy, a generalized correlation function inspired from Reyni's entropy, as a detection function to capture the instantaneous flux while preserving insensitiveness to outliers. Next, a novel peak picking algorithm is specially designed for this detection function. By calculating the fitness of a pre-defined inverse hyperbolic kernel to a detection function, it is possible to find an onset and its corresponding offset simultaneously. Experimental results show that the proposed method achieves performance significantly better than or comparable to other state-of-the-art techniques for onset detection in singing voice.

Metrical-accent Aware Vocal Onset Detection in Polyphonic Audio

“…As a baseline we run the algorithm of [14] with the 105 note states, we introduced in Section 4.1.2 3 . The note transition probability is the original as presented in Eq.…”

“…In multi-instrumental recordings, an essential first step is to extract reliably the predominant vocal melody. There have been few works dealing with SVT in multiinstrumental recordings in general [13,15], and with onset detection, in particular [3]. Some of them [13,15] rely on the algorithm for predominant melody extraction of [19].…”

“…Note that measuring transcription accuracy remains outside the scope of this study. 3 We ported the original VAMP plugin implementation to python, which is available at https://github.com/georgid/pypYIN 4 The evaluation script used is at https://github.com/CPJKU/madmom/blob/master/madmom/evaluation/beats.py 5 Note that the f-measure is agnostic to the phase of the detected beats, which is clearly not optimal 6 We used ). Mauch stands for the baseline, following the approach of [14].…”

Differential Evolutionary Particle Swarm Optimization for Load Adjustment Distribution State Estimation using Correntropy

“…Correntropy is a method to solve the problem of overall worsening of estimation results because of wrong values that are usually contained in least squares. The concept of correntropy is used in image analysis, 22 acoustic processing of voice, 23 and so on; in the field of power systems, there are studies on state estimation of transmission systems 24 and output forecasting of wind power generation. 25 Considering massive introduction of photovoltaic generation and other renewable energies, one has to take into account possibility of bad data that are cannot be classified as outliers.…”

Differential evolutionary particle swarm optimization for load adjustment distribution state estimation using correntropy

“…Correntropy is a method to solve the problem of overall worsening of estimation results because of wrong values that are usually contained in least squares. The concept of correntropy is used in image analysis, acoustic processing of voice, and so on; in the field of power systems, there are studies on state estimation of transmission systems and output forecasting of wind power generation . Considering massive introduction of photovoltaic generation and other renewable energies, one has to take into account possibility of bad data that are cannot be classified as outliers.…”