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This paper proposes a speech/music classification system based on i-vector. An analysis of two classification methods, namely cosine distance score (CDS) and support vector machine (SVM) is performed. Two session compensation methods, within-class covariance normalization (WCCN) and linear discriminant analysis (LDA) are also discussed. The performance of proposed systems yields better results compared...
Computational auditory scene analysis (CASA) system is well used in speech enhancement area in recent years. We propose a new system that combines CASA and spectral subtraction to get better enhanced speech. The CASA part consists of the latest method deep neural networks (DNNs). The original way to reconstruct the denoise signal is to use the estimated masks with direct overlap-add method ignoring...
This paper presents a phonetic analysis of Arabic speech language phonemes using hidden Markov model classifiers and their confusion matrices. For this purpose, a new classical Arabic speech corpus was planned and designed. The corpus is based on recitations from The Holy Quran of specific scripts. Semi-manual labeling and segmentation of the audio files along with other language resources such as...
This article proposes a gender and geographical origin recognition system for Arabic speakers based on the dialect and accent characteristics. We demonstrate that the speaker gender and nationality can be determined from colloquial Arabic speech and recommend that this system can be integrated to more complex biometric applications. The acoustic features of our proposed dataset used to identify the...
Singular Spectrum Analysis (SSA) is a nonparametric approach used to decompose a time series into meaningful components, related to trends, oscillations and noise. SSA can be seen as a spectral decomposition, where each term is related to an eigenvector derived from the trajectory matrix. In this context the eigenvectors can be viewed as eigenfilters. The frequency domain interpretation of SSA is...
User experience of 3D visualization on light field displays depends on several technical and human factors. One of these factors is Region of Interest, which determines the properties of visualization, such as the level of zoom. In this paper we present the results of three experiments investigating the effect of level of zoom on Quality of Experience. These experiments use different subjective quality...
Underwater computing systems have recently emerged as a new technology for underwater applications. In our previous work, we employed various nodes (processing nodes, gateway nodes, and sensing nodes) that are used to construct different candidate computing architectures (i.e. single, pipeline, and hybrid of parallel/pipeline). In this paper, we use these computing architectures in a real world scenario...
In this paper, we modify the classic manifold separation technique (MST), aiming to reduce its dependence on high signal-to-noise ratio (SNR) measuring environment. According to the analysis of the array response, it is demonstrated that to maintain a correct phase relationship between the received data at different calibration angles is indispensable for the application of MST. Thus, we slightly...
A major concern for Air traffic controllers (ATC) are facing on a daily basis are controlled Airspace (CAS) infringements. An infringement is when aircraft penetrates CASs without an advanced clearance from the ATC. These infringement may cause a conflict or a midair collision with a commercial aircraft flying within CAS. As a result, a ground based safety net called Controlled Airspace infringement...
The probability hypothesis density (PHD) filter is widely used to solve multi-target tracking (MTT) problems. Although the Sequential Monte Carlo (SMC) implementation provides a tractable solution for PHD filter to handle the highly nonlinear and non-Gaussian MTT scenario, the high computational cost caused by a large number of particles limits the applications that need to be performed in real-time...
We present a multi-target tracking system for estimating the position of multiple soccer players as they move around during a soccer game. Our system relies on silhouette observations recorded by a static camera, and utilises 3D models and particle filter methods to estimate athlete positions. Tracking parameters can be adapted in order to tip the scales towards precision or performance. We present...
Electricity demand time series are stochastic processes related to climate, social and economic variables. By predicting the evolution of such time series, electrical load forecasting can be performed in order to support the electrical grid planning. In this paper, we propose a Kalman based load forecasting system for daily demand forecasting. Our proposed approach incorporates a Principal Component...
Source apportionment is usually tackled with blind Positive/Non-negative Matrix factorization (PMF/NMF) methods. However, the obtained results may be poor due to the dependence between some rows of the second factor. We recently proposed to inform the estimation of this factor using some prior knowledge provided by chemists—some entries are set to some fixed values—and the sum-to-one property of each...
The problem of detecting an anomalous process over multiple processes is considered. We consider a composite hypothesis case, in which the measurements drawn when observing a process follow a common distribution parameterized by an unknown parameter (vector). The unknown parameter belongs to one of two disjoint parameter spaces, depending on whether the process is normal or abnormal. The objective...
Being a significant construct in a wide range of combinatorial problems, the k-subset sum problem (k-SSP) computes k-element subsets, out of an n-element set, satisfying a user-defined aggregation value. In this paper, we formulate the k-subset sum problem as a search (optimization) problem over the space of integers associated with combination elements. And by using rigorous computational experiments...
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