Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of compression ratio (CR), mean square error (MSE) and peak signal to noise ratio (PSNR) are assessed. Computer simulation results indicate that the two dimensions MCT offer a better compression ratio, MSE and PSNR than DWT.
Interpreting is a process adopted by a skillful and well qualified interpreter to convey orally the meaning from a source language into a target language simultaneously .In this process the interpreter has no time to think or check the exact meaning of the words, phrases and sentences. The main technique used by the interpreter is based on his/her competence .This type of translation is used in press conferences and political speeches of high rank figures.
This paper deals with analyzing the interpretation of Obama's farewell speech adopted by two authentic TV Channels(Sky News and AL- Jazeera).The aim of this paper is to investigate the quality of each interpreting by adopting Nida's (1996:164
... Show MoreThe expressive speech in the art of acting is considered to be the leading action for thinking and the interior interaction of the individual, in the organization of his relationship with the elements of the environment and its content, and the more acquired the individual's performance today skills in organizing and export of his conflicts and natural occasions , whenever , becomes more adaptable and an interpreted physically and acoustically inside pluralities in personalities, suited to the modern age. This research has addressed a range of topics related to expressive speech in the art of acting, since the first chapter included a systematic framework of the research, represented by the problem , the importance and aims of research t
... Show MoreA growing and pressing need for Speech Enhancement Algorithms (SEAs) has emerged with the proliferation of hearing devices and mobile devices that aim to improve speech intelligibility without sacrificing speech quality. Recently, a tremendous number of studies have been conducted in the field of speech enhancement. This study aims to map the field of speech enhancement by conducting a systematic literature review to provide comprehensive details of recently proposed SEAs. This systematic review aims to highlight research trends in SEAs and direct researchers to the most important topics published between 2015 and 2024. It attempts to address seven key research questions related to this topic. Moreover, it covers articles available
... Show MoreThis paper proposes a hybrid speech enhancement estimator that integrates the Perceptually-motivated Karhunen–Loève Transform (PKLT) with the Dual-Masking Harmonic-based (DMH) algorithm in a unified framework termed PKDMH. The main novelty lies in combining perceptual subspace projection with harmonic-residual suppression, enabling the system to jointly remove noise while preserving speech-relevant spectral cues. PKLT first performs perceptual subspace projection and suppresses inaudible components, after which DMH eliminates remaining broadband and harmonic residuals. The proposed PKDMH system was evaluated using the TIMIT dataset contaminated with five noise types: White, Pink, F16, Airport, and Car noise—across five SNR leve
... Show MoreEnergy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the
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