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Computational speech reconstruction algorithms have the ultimate aim of returning natural sounding speech to aphonic and dysphonic individuals. These algorithms can also be used by unimpaired speakers for communicating sensitive or private information. When the glottis loses function due to disease or surgery, aphonic and dysphonic patients retain the power of vocal tract modulation to some degree...
Smile is not only a visual expression. When it occurs together with speech, it also alters its acoustic realization. Being able to synthesize speech altered by the expression of smile can hence be an important contributor for adding naturalness and expressiveness in interactive systems. In this work, we present a first attempt to develop a Hidden Markov Model (HMM)-based synthesis system allowing...
In this paper, we expose our work on classification of smiled vowels, shaking vowels and laughter syllables. This work is part of a larger framework that aims at assessing the level of amusement in speech using only audio cues. Indeed all of these three categories occur in amused speech and are considered to express a different level of amusement. Four novel features are used to accomplish this task...
As improvements on acoustic modeling have rapidly progressed in recent years thanks to the impressive gains in performance obtained using deep neural networks (DNNs), language modeling remains a bottleneck for high performance large vocabulary continuous speech recognition (LVCSR) systems. In this paper an algorithm for automatic words extraction from a stream of phones is suggested to be used in...
Speech separation based on deep neural networks (DNNs) has been widely studied recently, and has achieved considerable success. However, previous studies are mostly based on fully-connected neural networks. In order to capture the local information of speech signals, we propose to use convolutional maxout neural networks (CMNNs) to separate speech and noise by estimating the ideal ratio mask of the...
Discovering causal relationships among a set of observed variables is a very important and essential problem in science. In many fields, predicting causes can help to avoid harmful consequences. Learning Bayesian network (BN), and Randomized Controlled Trials (RCTs) play a major role in Causal discovery. Existing algorithms fail to discover causal relationships on non-fixed structures, the cost of...
Embedded systems have become very important in our life; they pervade all fields in today's advanced technology. With the increasing importance of these systems, designers need to estimate the performance metrics such as Delay which includes processing and communication and Power consumption. This procedure is very critical and even crucial at an early stage of design and implementation. Using GPUs...
Causal discovery is a well-studied problem due to an urgent need for systems that predict, explain, and make proper and necessary decisions in many domains including epidemiology, biology, medicine, economics, physics, and social sciences. Existing techniques such as learning Bayesian networks (BNs) and Randomized controlled trials (RCTs) are expensive and time consuming. In addition, they only find...
Twitter sentiment analysis has become an effective way in measuring public sentiment about a certain topic or product. Thus, researchers have worked extensively in recent years to build efficient models for sentiment classification. In this paper, we will measure the effect of varying the training set size on the classification accuracy and F-score of SVM and Naive Bayes classifiers. We will expand...
According to a recent survey by the World Economic Forum: The Global Information Technology Report 2014, several Gulf Cooperation Council states have continued their efforts to improve ICT uptake and better integrate ICT into more robust innovation ecosystems in order to obtain higher returns. For example, the UAE now ranks 24th and KSA ranks 32nd in the world. In this research paper, we conduct a...
One of the most important factors in human-computer interaction is the user emotional reaction. Interactive environments including serious games that are responsive to user emotions improve their effectiveness and user acceptances. Testing and training for user emotional competence is meaningful in health care, which has motivated us to analyze immersive affective games using feedback. In this article,...
Passive bistatic radar (PBR) systems exploit communication signals available in the environment for surveillance and tracking applications. Currently, GSM mobile communication signals are almost everywhere specially in the populated areas and road networks. PBR systems based on GSM signals are quite suitable for short-range surveillance systems. But the low-bandwidth of the signal results in low range...
Passive bistatic radar (PBR) systems use existing RF broadcast and communication signals in the environment. Currently, GSM mobile communication signals are almost ubiquitous particularly in the populated areas and road networks. Thus, GSM based PBR systems are suitable for short-range surveillance systems. But, like many communication waveforms, these signals are low-bandwidth signals resulting in...
This paper presents a novel approach to the adaptive tracking of maneuvering targets using Kalman filter. The adaptation technique is achieved by constructing a pursuing system of two stages. The first stage comprises a vector Kalman filter of three states undergoes some biasing drift or mismodeling during a target evasive maneuver. While the second stage consists of a scalar Kalman filter basically...
The digital beamforming (DBF) of ultra-wideband (UWB) radar is a challenging issue and its performance is closely affected by the delay compensation filters and the aperture of the antenna array. In this paper, a high-resolution DBF method for UWB signals utilizing Hermite fractional delay filter sets combining a virtual array created by a vector extrapolation algorithm on autoregressive(AR) models...
A current ground based safety net called Controlled Airspace infringement Tool (CAIT) is used by Air Traffic Controllers (ATCs). It warns them if any aircraft within uncontrolled airspace penetrates the Controlled airspace (CAS) without an advance clearance from the ATC. This penetration or ‘Infringement’ is considered as a major concern to ATCs where it may cause a possible conflict or mid-air collision...
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