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An In-Depth Review of Speech Enhancement Algorithms: Classifications, Underlying Principles, Challenges, and Emerging Trends
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Speech enhancement aims to improve speech quality and intelligibility in noisy environments and is important in applications such as hearing aids, mobile communications and automatic speech recognition (ASR). This paper shows a structured review of speech enhancement techniques, classified depending on the channel configuration and signal processing framework. Both traditional and modern approaches are discussed, including classical signal processing methods, machine learning techniques, and recent deep learning-based models. Furthermore, common noise types, widely used speech datasets, and standard evaluation metrics for evaluating speech quality and intelligibility are reviewed. Key challenges such as non-stationary noise, data limitations, reverberation, and generalization to unseen noise conditions are highlighted. This review presents the advancements in speech enhancement and discusses the challenges and trends of this field. Valuable insights are provided for researchers, engineers, and practitioners in the area. The findings aid in the selection of suitable techniques for improved speech quality and intelligibility, and we concluded that the trend in speech enhancement has shifted from standard algorithms to deep learning methods that can efficiently learn information regarding speech signals.

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
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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

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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Speech Emotion Recognition Using MELBP Variants of Spectrogram Image
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Publication Date
Mon Mar 27 2023
Journal Name
Iranian Journal Of Materials Science And Engineering
First-Principles Analysis of Cr-Doped SrTiO 3 Perovskite as Optoelectronic Materials
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The influence of Cr3+ doping on the ground state properties of SrTiO 3 perovskite was evaluated using GGA-PBE approximation. Computational modeling results infered an agreement with the previously published literature. The modification of electronic structure and optical properties due to Cr3+ introducing into SrTiO 3 were investigated. Structural parameters assumed that Cr3+ doping alters the electronic structures of SrTiO 3 by shifting the conduction band through lower energies for the Sr and Ti sites. Besides, results showed that the band gap was reduced by approximately 50% when presenting one Cr3+ atom into the SrTiO 3 system and particularly positioned at Sr sites. Interestingly, substituting Ti site by Cr3+ led to eliminating the ban

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Publication Date
Mon Jun 01 2026
Journal Name
Wasit Journal Of Engineering Sciences
Engineering Perspectives on Rehabilitation Robotics: An Integrative Review of Control Strategies, Optimization Methods, and IoT-Enabled Platforms
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Rehabilitation robotics has developed into an interdisciplinary field which uses mechanical design and control theory and optimization techniques together with information technologies to create better recovery results for people who suffer from motor disabilities. The present review assesses rehabilitation robotics research through engineering application studies which use more than 120 peer-reviewed articles published between 2014 and 2024. The discussion covers four main areas which include control strategies that start from basic PID methods and extend to sophisticated adaptive and intelligent control systems. The study utilizes bio-inspired and metaheuristic optimization methods to enhance system functionality and develop control paths

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Publication Date
Thu Dec 15 2022
Journal Name
Al-academy
Inventory of Saudi youth trends towards choosing fashion accessories
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This research aims to determine the Attitudes Towards Fashion accessories of Saudi youth, and the descriptive analytical method was used in this research. The research sample was 500 youth in Riyadh that age between 20 to less than 40.  The most important results show that young people prefer shoes by 53.2%, that 45.2% of young people prefer acquiring modern designs in fashion accessories, and the research emphasized the importance of studying the impact of rapid economic, social and cultural developments on young people’s attitudes towards fashion and its accessories, directing the attention of Saudi fashion designers towards complements Fashion to offer designs that match their trends

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Publication Date
Sat Jul 06 2013
Journal Name
Creative Construction Conference 2013
The challenges of governing public private partnership in Iraq infrastructure projects
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Public-private partnership (PPP) has been used over the past 20-30 years by governments in developed countries to meet the public demand for infrastructural services. In Iraq, the PPP concept is comparatively new to the Government of Iraq (GoI), where the government has historically taken most of the responsibility for providing public services. There are few PPP projects in Iraq. However, the number is increasing. Recently the Iraqi market has experienced a number of attempts of PPP in different sectors, especially after the new investment law in 2006. The aim of this paper is to evaluate the investment environment in Iraq and to indicate the main factors affecting PPP in particular for infrastructure projects. Some literature review and

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Publication Date
Sun Jun 30 2024
Journal Name
Journal Of Language Studies
Translation Challenges in Children's Literature: A Comparative Study of Story Narratives
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This paper presents the intricate issues and strategies related to the translation of children's books, and it particularly focuses on the comparative analysis of "The Tale of Peter Rabbit" by Beatrix Potter and "Le Petit Prince" (The Little Prince) by Antoine de Saint-Exupéry. The study finds that the typical problems in translation are, idiomatic expressions, cultural reference, and the voice preservation, along side-sheet-specific challenges which each of the text faces. The translator of Potter's work should have skills of transposing all culturally oriented peculiarities of the UK land to the international audience to keep it accessible. On the contrary, "Le Petit Prince" translation will be the process of capturing the abstra

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Publication Date
Tue Mar 31 2026
Journal Name
Magna Scientia Advanced Research And Reviews
Bombay and para-Bombay blood group phenotypes: Molecular basis, epidemiology, diagnosis, and transfusion management: An extended review
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Bombay (Oh) and Para-Bombay are rare variants of the ABO blood group system that carry significant clinical importance. They are characterized by the absence or a marked reduction in the expression of the H antigen on red blood cells (RBCs). This deficiency leads to a failure in the synthesis of A and B antigens, predisposing patients—particularly those with the Bombay phenotype—to developing potent anti-H antibodies, which can cause severe hemolytic transfusion reactions. Objective: The primary goal is to provide clinicians and laboratory specialists with a practical and comprehensive framework to prevent avoidable blood mismatch and improve clinical outcomes for patients suffering from H-deficient phenotypes. Methods: This rev

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Publication Date
Tue May 16 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets
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Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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