Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the
... Show MoreThe main goal of this paper is to introduce and study a new concept named d*-supplemented which can be considered as a generalization of W- supplemented modules and d-hollow module. Also, we introduce a d*-supplement submodule. Many relationships of d*-supplemented modules are studied. Especially, we give characterizations of d*-supplemented modules and relationship between this kind of modules and other kind modules for example every d-hollow (d-local) module is d*-supplemented and by an example we show that the converse is not true.
Students' passive listening to their teacher's reading is one of main
reasons behindtheir weakness in the reading skill which in its turn may
hinderachieving the in desired objectives.
When exploiting critical thinking, which will lead to deeper
understanding of the intellectual content, in learning and accurate and
correct students' outcomes.
Active listening allows paying attention to the speaker, asking him,
arguing with him, judging what he says, and making decision on what
he says. For this reason, the researcher felt the need for preforming a
study to identify the effect of critical listening on developing students'
critical thinking at reading in the Kurdish language department.
The researcher has
The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
The risk of significant concern is resistance to antibiotics for public health. The alternative treatment of metallic nanoparticles (NPs), such as heavy metals, effects on antibiotic resistance bacteria with different types of antibiotics of - impossible to treat using noval eco-friendly synthesis technique nanoparticles copper oxide (CuO NPs) preparation from S. epidermidis showed remarkable antimicrobial activity against S.aureus Minimum inhibitory concentra range (16,32,64,256,512) µg/ml via well diffusion method in vitro, discover those concentrations effected in those bacteria and the best concentration is 64 µg/ml, characterization CuO NPs to prove this included atomic force microscope, UV, X-ray Diffraction and TEM, and ant
... Show MoreIn this paper, we consider the problem of stochastic project network when some or all activities are interrupted. An approach has been built to schedule the critical activities, by constructing some expressions based on the project lateness costs due to the interruption activities. Two simple example are presented to validate our approach.
Key words: Project Management, Project scheduling, Stochastic activity duration, Stochastic PERT.
Introduction
Recently, Projects planning and optimal timing, under uncertainty are extremely critical for many organizations, see [19]. Having an effective mathematical model wi
... Show MoreSpeech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra