16 accepted papers
Sound zone control enables different users to enjoy different audio contents in the same acoustic environment. Generalized eigenvalue decomposition (GEVD)-based methods allow us to control the tradeoff between the acoustic contrast (AC) and signal distortion (SD). However, such methods have a high c…
In this paper, a method for estimating the autoregressive parameters from a signal segment is proposed. The method is based on a deep neural network (DNN) in combination with the classical Levinson-Durbin recursion (LDR). The DNN acts as a pre-processor for the LDR and can be trained on different me…
Most parametric fundamental frequency estimators make the implicit assumption that any corrupting noise is additive, white Gaus-sian. Under this assumption, the maximum likelihood (ML) and the least squares estimators are the same, and statistically efficient. However, in the coloured noise case, th…
This paper deals with the influence of pre-whitening for the task of fundamental frequency estimation in noisy conditions. Parametric fundamental frequency estimators commonly assume that the noise is white and Gaussian and, therefore, they are only statistically efficient under those conditions. Th…
The understanding of speech from a particular speaker in the presence of other interfering speakers can be severely degraded for a hearing impaired person. Beamforming techniques have been proven to be effective to improve the speech understanding in such scenarios. However, the number of microphone…
The creation of sound zones has been an active research topic for approximately two decades. Many sound zone control methods have been proposed, and the best approaches result in a target to interferer ratio (TIR) of about 15 dB in a practical set-up. Unfortunately, this is far from a TIR of about 2…
The estimation of the noise power spectral density (PSD) forms a critical component of several existing single channel speech enhancement systems. In this paper, we evaluate one new and some of the existing and commonly used noise PSD estimation algorithms in terms of the spectral estimation accurac…
Sound zones are typically created using Acoustic Contrast Control (ACC), Pressure Matching (PM), or variations of the two. ACC maximizes the acoustic potential energy contrast between a listening zone and a quiet zone. Although the contrast is maximized, the phase is not controlled. To control both…
Recently, so-called smart speakers have been introduced and they include a microphone array. One potential application of such a smart speaker is to use it for calibrating a larger audio system which the speaker is a part of. In this paper, we propose a method to perform this calibration using one o…
Most speech enhancement algorithms need an estimate of the noise power spectral density (PSD) to work. In this paper, we introduce a model-based framework for doing noise PSD estimation. The proposed framework allows us to include prior spectral information about the speech and noise sources, can be…
Pitch estimation is an important task in speech and audio analysis. In this paper, we present a multi-pitch estimation algorithm based on block sparse Bayesian learning and intra-block clustering for speech analysis. A statistical hierarchical model is formulated based on a pitch dictionary with a f…
The harmonic chirp signal model has only very recently been introduced for modelling approximately periodic signals with a time-varying fundamental frequency. A number of estimators for the parameters of this model have already been proposed, but they are either inaccurate, non-robust to noise, or v…
In this paper, we present a greedy subspace method for the acoustic echoes labeling problem, which occurs in applications such as source localization and room geometry estimation. The orthogonal projection into the null space of the microphones position matrix is used to filter and sort all possible…
Reverberation is well-known to have a detrimental impact on many localization methods for audio sources. We address this problem by imposing a model for the early reflections as well as a model for the audio source itself. Using these models, we propose two iterative localization methods that estima…
Fundamental frequency estimation is a very important task in many applications involving periodic signals. For computational reasons, fast autocorrelation-based estimation methods are often used despite parametric estimation methods having superior estimation accuracy. However, these parametric meth…
Time-difference-of-arrival (TDOA) estimation is an important problem in many microphone signal processing applications. Traditionally, this problem is solved by using a cross-correlation method, but in this paper we show that the cross-correlation method is actually a restricted special case of a mu…