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Aliasing is major problem in any audio signal processing chain involving nonlinearity. The usual approach to antialiasing involves operation at an oversampled rate—usually 4 to 8 times an audio sample rate. Recently, a new approach to antialiasing in the case of memoryless nonlinearities has been proposed, which relies on operations over the antiderivative of the nonlinear function, and which allows...
Separating an acoustic signal into desired and undesired components is an important and well-established problem. It is commonly addressed by decomposing spectral magnitudes after exponentiation and the choice of exponent has been studied from numerous perspectives. We present this exponent selection problem as an approximation to the actual underlying geometric situation. This approach makes apparent...
One goal of Virtual Analog modeling of audio circuits is to produce digital models whose behavior matches analog prototypes as closely as possible. Discretization methods provide a systematic approach to generate such models but they introduce frequency response error, such as frequency warping for the trapezoidal method. Recent work showed how using different discretization methods for each reactive...
Human and machine performance in acoustic scene classification is examined through a parallel experiment using TUT Acoustic Scenes 2016 dataset. The machine learning perspective is presented based on the systems submitted for the 2016 challenge on Detection and Classification of Acoustic Scenes and Events. The human performance, assessed through a listening experiment, was found to be significantly...
In this paper we propose a method for the localization of acoustic sources using small microphone arrays randomly placed in the acoustic scene. The presented approach is based on a ray-based plane wave decomposition performed locally on each microphone array followed by a fusion of the obtained results in order to build a sound field representation that is convenient for the localization of acoustic...
We propose in this paper a simple, yet efficient multi-channel fusion framework for joint acoustic event detection and classification. The joint problem on individual channels is posed as a regression problem to estimate event onset and offset positions. As an intermediate result, we also obtain the posterior probabilities which measure the confidence that event onsets and offsets are present at a...
The separation of acoustic signals is often accomplished through subtractive decompositions of frequency-domain representations. This is typically enabled by the zero phase approximation or the un-correlated signals approximation but both of these are very coarse approximations in the mathematical sense. We investigate this disconnect between what works in practice and what is mathematically correct...
In this paper, we propose a novel approach to multizone sound reproduction, which is motivated by the Kirchhoff-Helmholtz integral equation and aims at the simultaneous optimization of the sound pressure and particle velocity vector on contours around multiple local listening areas. The benefit of this approach is that the control points do not need to be distributed within the local listening areas,...
Let us consider a specific acoustic scene appearing in a continuous audio stream recorded while making a trip a in city. In this work, we aim at detecting at the earliest opportunity the several occurrences of this scene. The objective in early detection is then to build a decision function that is able to go off as soon as possible from the onset of a scene occurrence. This implies making a decision...
Audio signal processing has long been the obvious approach to problems such as microphone array processing, active noise control, or speech enhancement. Yet, it is increasingly being challenged by black-box machine learning approaches based on, e.g., deep neural networks (DNN), which have already achieved superior results on certain tasks. In this talk, I will try to convince that machine learning...
A mapping system based on an artificial neural network was designed, trained, and tested to map Arabic acoustic parameters to their corresponding articulatory features. The main objective of the study was to find the correlation between these two different types of features. To train and test the system, an in-house database was created for all 29 Arabic alphabets as carrier words for our intended...
This paper presents two families of distances in the space of high order proximity networks. The distances measure differences between networks and are shown to be valid metrics in the space of high order proximity networks modulo permutation isomorphisms. Practical implications are explored by comparing the coauthorship networks of two popular signal processing researchers. The metrics succeed in...
In this paper, an empirical evaluation of acoustical signals for leakage detection and quantification in underground plastic pipes for main water distribution networks is presented. Several experiments have been carried out to collect acoustic signals generated from various leakage volumes. Upon signals analysis, it is noticed that the acquired signals are so weak and they are buried in the background...
Recently, many adaptive filtering proposals that discuss the sparsity of the system have been appeared. These proposals are, mainly, based on the least-mean-square (LMS) algorithm. In this paper we propose two algorithms that exploit the sparsity of the system and based on the mixed norm LMS (MN-LMS) algorithm. The first algorithm is proposed by adding l1-norm penalty to the cost function of the MN-LMS...
Higher order acoustic sensors rely on the spatial gradients of the acoustic pressure field for achieving high directivity. Two practical methods for realizing higher order acoustic sensors using acoustic vector sensor arrays are presented. The first method relies on short linear arrays of closely spaced 2-D vector sensors. The second method is based on the particle velocity measurements obtained along...
Open-spherical acoustic intensity probes are microphone arrays based on the Kirchhoff-Helmholtz integral and are used in the measurement of active acoustic intensity. The acoustic intensity measurements obtained by these arrays can be used to localise sound sources. Previously, the performance of these arrays in acoustic free field conditions were obtained using numerical simulations and it was shown...
In this paper, a gunshot detection system prototype designed and produced in MİKES Inc., will be mentioned. The system has five subsystems, a reference microphone unit, a central unit and a user computer. Although 26 microphones are employed in the prototype, the system hardware background supports synchronous processing of 256 microphone data. Each subsystem on its own has the capability of finding...
In this document, our latest work on distance estimation algorithm of acoustic based shot estimation system will be discussed. Information about our 4 point sensor array and the omni-directional microphones will be provided. Using Gaussian Mixture Models, a voice activity detection front end is designed. When a shot is detected, critical raw data is processed for directional measurement using generalized...
An audio recording, made in a real environment, carries an acoustical signature which changes according to the acoustical characteristics of the environment and the recording positions. This signature which is similar to a 3D room impulse response contains the directions, levels and arrival times of the direct source and reflections. Although it is easy to obtain reverberant recordings by convolving...
The Ninth Annual Machine Learning for Signal Processing (MLSP) Data Competition Committee has hosted a bird classification challenge at Kaggle.com (http://www.kaggle.com/c/mlsp-2013-birds). For this year's competition, participants were asked to develop classification algorithms to reliably identify the set of bird species in real-world audio data collected in an acoustic monitoring scenario. In this...
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