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Audio Classification Based on Content Features
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Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to those gotten from other popular methods inthis field, such as Zero Crossing Rate (ZCR), Amplitude Descriptor (AD), Short Time Energy (STE), and Volume (Vo). The test results indicated, that the attained averageaccuracy of classification is improved up to94.9232% for training set and 95.8666%for testing set.The classification performance of these two extracted featuresets is studied individually, and then they used together as one feature set. Theiroverall performance is investigated, the test results showed that the proposed methods give high classification rates for the audio.

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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Isolation and Classification of Green Alga Stigeoclonium attenuatum and Evaluation of its Ability to Prepare Zinc Oxide Nanoflakes for Methylene Blue Photodegradation by Sunlight
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           Algae have been used in different applications in various fields such as the pharmaceutical industry, environmental treatments, and biotechnology. Studies show that the preparation of nanoparticles by a green synthesis method is a promising solution to many medical and environmental issues. In the current study, the green alga Stigeoclonium attenuatum (Hazen) F.S. Collins 1909 was isolated and identified from the Al-Hillah River (Governorate of Babylon) in the middle of Iraq. The green synthesis by the aqueous extract of algae was used to prepare the nanoflakes of ZnO. Nanoflakes of ZnO are characterized by X-Ray diffraction (XRD) and scanning electron microscope (SEM) with flakes shape and dimensions ranging be

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
الصوت ووجوه الاعجاز القرآني سورة القدر میدانا تطبیقیا (دراسة اسلوبیة)
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This research has been written as a fullfillment of the researchers
desire of joining the qurannic convoy servos each one from his own place and
this own field of specialization . she has found that the holly quraan is a
parctical field for theories and rules of old and modren phonetic studies also
she has becom a ware of the fact that the quraanic Important –making has
various aspects that neither can be a ware of nor can be vanished by the
courses of ages for science can flourish and reach tops to the extent they
don’t accept any new addition theories can be studied and given laws at last
except the quannice important – making which is new and discovered at
deferent times and places in spite of the shor

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of The College Of Languages (jcl)
Ali Şir Nevai Muhakemetül-lugateyn Eserinin Sesbilimi Özellikleri
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Önsöz
Ali Şir Nevai’nin vücuda getirdiği edebi Çağatayca, edebi ve canlı bazı Türk şivelerinin işlenmesinden ve kaynaşmasından hasıl olmuştur. Bu gün bu dilin
fonetik bünyesi hakkında, en çok bilgi veren, yine Nevai’nin kendisidir. Onun―Muhakeemet-ül-luğateyn‖ adlı eseri, bu bakımından büyük bir değer taşımaktadır.Bu eserinde Nevai, bir taraftan Türk dilinin Farsçaya üstünlüğünü ispata kalkışken, bir taraftan da kendi Türkçesinin fonetik ve morfolojik özelliklerini belirtmiştir. O, Arab imlası kaidesi üzerine ayni şekilde yazılarak, semantik yönden başka başka manalarda kullanılan kelimeleri sıralarken, açık bir surette, edebi Çağataya şivesinin fonetik bünyesini d

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Scopus (11)
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Publication Date
Fri Jan 01 2021
Journal Name
Communications In Computer And Information Science
Audio Compression Using Transform Coding with LZW and Double Shift Coding
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Home New Trends in Information and Communications Technology Applications Conference paper Audio Compression Using Transform Coding with LZW and Double Shift Coding Zainab J. Ahmed & Loay E. George Conference paper First Online: 11 January 2022 126 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1511) Abstract The need for audio compression is still a vital issue, because of its significance in reducing the data size of one of the most common digital media that is exchanged between distant parties. In this paper, the efficiencies of two audio compression modules were investigated; the first module is based on discrete cosine transform and the second module is based on discrete wavelet tr

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Publication Date
Thu Jan 04 2018
Journal Name
Journal Of Electrical Engineering And Technology
An efficient selective method for audio watermarking against de-synchronization attacks
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Publication Date
Tue Jul 18 2023
Journal Name
Journal Of Current Researches On Social Sciences
A Study on Sociocultural Features among Turkish and Iraqi Women
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SM ADAI, BN RASHID, Journal of Current Researches on Social Sciences, 2023

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Publication Date
Thu Nov 01 2012
Journal Name
Ijcsi International Journal Of Computer Science
Implementing a novel approach an convert audio compression to text coding via hybrid technique
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Compression is the reduction in size of data in order to save space or transmission time. For data transmission, compression can be performed on just the data content or on the entire transmission unit (including header data) depending on a number of factors. In this study, we considered the application of an audio compression method by using text coding where audio compression represented via convert audio file to text file for reducing the time to data transfer by communication channel. Approach: we proposed two coding methods are applied to optimizing the solution by using CFG. Results: we test our application by using 4-bit coding algorithm the results of this method show not satisfy then we proposed a new approach to compress audio fil

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Publication Date
Tue Oct 30 2018
Journal Name
Companion Of The 2018 Acm Conference On Computer Supported Cooperative Work And Social Computing
Collaborative Content Creation
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Modern education incorporates strong elements of collaborative learning: activities that prompt students to collaborate on completing learning tasks. In this work we investigate the relationship between media type and student collaboration and attribution patterns during collaborative content creation. We run similarity analyses on text and video artifacts submitted by students as part of collaborative exercises in an undergraduate module. Our main finding is that the same cohort of students was significantly more likely to attribute non-original content to its sources when authoring text compared to video content and when this content is not produced by a peer student. Our preliminary results based on only two media suggest that media type

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