This paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its universality and lack of complexity on the sensor side. In this paper a study of applying compressed sensing on audio signals was presented. The performance of different bases and its reconstruction are investigated, as well as exploring its performance. Simulations results are present to show the efficient reconstruction of sparse audio signal. The results shows that compressed sensing can dramatically reduce the number of samples below the Nyquist rate keeping with a good PSNR.
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الحمدُ للهِ رب العالمين ، والصلاة والسلام على نبيه الأمين محمد r وعلى آله الطيبين الطاهرين ، وأصحابه الغر الميامين:
تعد الصورة السمعية مفهوما بيانيا نجده في البلاغة العربية واضحاً مؤثرا، مؤديا دورا جوهريا في إيصال الفكرة التي يروم الأديب إيصالها إلى المتلقي ولا تبدو السمعية واضحة إلاّ إذا نظر إليها في حالة أدبيه تهز كيان الشاعر  
... Show MoreStenography is the art of hiding the very presence of communication by embedding secret message into innocuous looking cover document, such as digital image, videos, sound files, and other computer files that contain perceptually irrelevant or redundant information as covers or carriers to hide secret messages.
In this paper, a new Least Significant Bit (LSB) nonsequential embedding technique in wave audio files is introduced. To support the immunity of proposed hiding system, and in order to recover some weak aspect inherent with the pure implementation of stego-systems, some auxiliary processes were suggested and investigated including the use of hidden text jumping process and stream ciphering algorithm. Besides, the suggested
... Show MoreTechnologies of the theatre show elements get great transferring concerning the creative embodiment of its aesthetic elements including its raws, forms, parts and masses in an attempt to achieve the prin cipal expressive progress to embody the main theme of the idea and the intended subject .
This is within the criterion of supporting the way to deal with technologies (décor elements , lighting music tones vocal affects , fashion and makeup) that achieving the emagintional appropriate atmosbheres which the writer and the director of the theatre show aim to make it present and succeed by furming active participation tunches of the ability of the cinogra . phic – element dsigners in order to invlve the theatre space atmospheres in cl
In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to t
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In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
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