Multi-Pitch Estimation

A Bayesian Approach for Single Channel Speech Separation

“…The CASA methods are fast and could be implemented in real time. There are, however, challenges that limit the pitch tracking performance for a mixture [5]: (1) Most existing pitch estimation methods perform reliably only with clean speech signals that have a single pitch track or harmonically related sinusoids [9] with almost no background interference [10]. (2) It is possible to perform a reliable pitch estimation using a mixture of a dominant (target) and a weaker (masking) signal as long as the pitches of the masking and target speech are different in a short frame [6].…”

An iterative subspace-based multi-pitch estimation algorithm

“…Numerous algorithms have been proposed see, e.g. [1][2][3][4][5][6][7]. In real recorded signals, however, multi-pitch scenarios occur more frequently than single-pitch scenarios.…”

“…In real recorded signals, however, multi-pitch scenarios occur more frequently than single-pitch scenarios. A number of multi-pitch algorithm are described in [6,3,4,1], to which we refer the interested reader.…”

“…The problem is to estimate o k from x(n) with N measured samples. The estimation problem associated with the real case can be cast as (1) by the use of analytic signals, which is valid when there is little or no spectral content of interest near 0 and p. In this paper, we assume that the number of sources K and the model orders L k of the individual sources are known, order estimation can be achieved with multi-dimensional search of the extended cost function [1,5].…”

“…Recently, subspace-based fundamental frequency estimators have shown good estimation performance both for single and multi-pitch cases [5,1,8]. This type of methods is forming a cost function by exploiting the orthogonality properties between the noise and signal subspaces decomposed from a covariance matrix.…”