A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of the compressed signal relative to the size of the uncompressed signal. The proposed algorithms where fulfilled with the use of Matlab package
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This research deals with the phenomenon of a similar voice phenomenon has founded
its own laws similar and includes the following phenomenon:
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between language and reading and then apply the provision in sura blessed.
Phenomenon Alaalal and substitution, Two of the important acoustic phenomenon the
linguistic heritage has shown Alaalal types and the difference between him and the
substitution then counted their applications in Sura.
Similar phenomena: in name and deed shares bult causes and probability voices and
sound that refrais where tilt.
Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio
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Considering the science of speech in the light of its purposes is an accurate scientific study that looks at it from its reality in which it originated, and its topic that it dealt with and its goals that it sought, and it follows its main course in the directions of approving the belief and inferring it, and repelling the objections to it, and this study comes to show the realism of the science of speech in its emergence Its subject and method, since its launch was from the reality of the Islamic nation and based on its intellectual needs, so its presence was necessary in the life of the Islamic nation because of its role in facing the challenges faced by the Islamic faith, and the dangers it was exposed to as a result of the intellectu
... Show MorePolitical speeches are represented in different shapes as political forum, events or as inaugural speech. This research critically analyzes the inaugural Speech of the President Donald Trump which was delivered on 20th ,January, 2017 from the site<www.cnn.com> retrieved on 10th ,May,2017. The objectives of the study are: First: classifying and discussing well known micro structures (linguistic feature) of the speech, and second: classifying the macro structures i.e. the delivered political inaugural speech in which he includes social structures. To reach to the objectives of the study, the researcher will adopt Norman Fairclough’s three dimensional Analytical Model(
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In this paper, we will focus to one of the recent applications of PU-algebras in the coding theory, namely the construction of codes by soft sets PU-valued functions. First, we shall introduce the notion of soft sets PU-valued functions on PU-algebra and investigate some of its related properties.Moreover, the codes generated by a soft sets PU-valued function are constructed and several examples are given. Furthermore, example with graphs of binary block code constructed from a soft sets PU-valued function is constructed.
Ischemic stroke is a significant cause of morbidity and mortality worldwide. Autophagy, a process of intracellular degradation, has been shown to play a crucial role in the pathogenesis of ischemic stroke. Long non-coding RNAs (lncRNAs) have emerged as essential regulators of autophagy in various diseases, including ischemic stroke. Recent studies have identified several lncRNAs that modulate autophagy in ischemic stroke, including MALAT1, MIAT, SNHG12, H19, AC136007. 2, C2dat2, MEG3, KCNQ1OT1, SNHG3, and RMRP. These lncRNAs regulate autophagy by interacting with key proteins involved in the autophagic process, such as Beclin-1, ATG7, and LC3. Understanding the role of lncRNAs in regulating auto
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