Özaydın, Selma
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Ozaydin, S.
Ozaydin, Selma
Ozaydin, Selma
Job Title
Dr. Öğr. Üyesi
Email Address
Main Affiliation
08.02. Çankaya Meslek Yüksekokulu
Çankaya Meslek Yüksekokulu
08. Meslek Yüksekokulları
01. Çankaya Üniversitesi
Çankaya Meslek Yüksekokulu
08. Meslek Yüksekokulları
01. Çankaya Üniversitesi
Status
Former Staff
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ORCID ID
Scopus Author ID
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Sustainable Development Goals
13
CLIMATE ACTION
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
3
GOOD HEALTH AND WELL-BEING
0
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15
LIFE ON LAND
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17
PARTNERSHIPS FOR THE GOALS
0
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14
LIFE BELOW WATER
1
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4
QUALITY EDUCATION
0
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11
SUSTAINABLE CITIES AND COMMUNITIES
0
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6
CLEAN WATER AND SANITATION
0
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10
REDUCED INEQUALITIES
0
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9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
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12
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0
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2
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1
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Research Products
7
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1
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5
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16
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Scholarly Output
18
Articles
11
Views / Downloads
1630/717
Supervised MSc Theses
0
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0
WoS Citation Count
6
Scopus Citation Count
27
WoS h-index
2
Scopus h-index
3
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0
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0
WoS Citations per Publication
0.33
Scopus Citations per Publication
1.50
Open Access Source
6
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0
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| Journal | Count |
|---|---|
| 2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022 -- 2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022 -- 23 November 2022 through 25 November 2022 -- Ras Al Khaimah -- 185596 | 3 |
| Open Journal of Modern Linguistics | 3 |
| Avrupa Bilim ve Teknoloji Dergisi | 1 |
| Fluctuation and Noise Letters | 1 |
| Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi | 1 |
Current Page: 1 / 3
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18 results
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Now showing 1 - 10 of 18
Article Investigation of Factors Affecting Noise Robustness in Voice Activity Detectors(Gazi Univ, Fac Engineering Architecture, 2023) Ozaydin, SelmaIn this manuscript, some voice activity detectors (VADs) in the literature were examined in terms of factors affecting their robustness under different acoustic noise conditions and in this context, the changes in detection accuracy rates according to changing noise conditions were tested. In this scope, the effect of situations such as whether the threshold value used in the decision phase in VAD methods is fixed or adaptive, the analysis window is short or long, the use of more than one feature vector together has been evaluated and analyzed comparatively. While three of the four different VAD detectors examined in this manuscript use feature vectors within the short-term analysis window while generating the decision result, one decides according to the measurement result of long-term spectral vectors. The VAD detectors in the article have been tested using the NOIZEUS noisy speech database. Thus, the performance of the analyzed VADs has been evaluated under different acoustic conditions using an extensive database that has already taken place in the literature. During the testing of the analyzed VADs, different input noise speech signals with environmental background noises between [15-0dB] such as restaurant, car, street, or station were tested. Tests were carried out using objective test measurement methods and the detection accuracy rate of each VAD method was measured. The results showed that each method gave different endurance performance in adverse environmental conditions.Article Comparative Analysis of Early Studies on Turkish Whistle Language and a Case Study on Test Conditions(2018) Özaydın, SelmaThis paper examines the early studies on Turkish Whistle Language and it argues that they have some controversial results. The study considers these issues need to be discussed and searched again in terms of linguistic and phonetic form. Unfortunately, there are few research studies on Turkish whistle language and most of them were performed nearly fifty years ago despite the fact that this language still has been used in Kuskoy region. Therefore, the findings of these early research studies could give valuable information to start to a new research study on the subject. The first scientific study on Turkish Whistle language was performed by a French scientist R.G. Busnel with his multidisciplinary research team in 1967. Some of this research’s results were published in the book. A Turkish scientist O. Baskan also participated in Busnel’s research group and published a paper on TWsL in 1968. However, some assertions such as people having a tendency to understand the Turkish whistle language with three vowels and three consonants have not been in the research results of R.G. Busnel. In addition, a Turkish scientist D. Aksan in Turkey had performed another research at Kuskoy region with his own team. Their test methods were different from the previous ones. This paper analyzes these research results on a comparative basis and presents the common and conflicted issues to discuss the uncertain points. The comparative evaluation of these past research studies aims to highlight the controversial position of the results on Turkish Whistle Language. In this scope, this paper opens a discussion about the selection of test conditions for an acoustic and linguistic analysis of the Turkish whistle language.Conference Object Citation - Scopus: 9Speech Denoising With Maximal Overlap Discrete Wavelet Transform(Institute of Electrical and Electronics Engineers Inc., 2022) Ozaydin, S.; Alak, I.K.In this paper, the effectiveness of the maximum overlapping discrete wavelet transform (MODWT) method on denoising the speech signal is tested and examined. Ensuring the intelligibility of the speech signal in noisy environments by separating it from the noise is a widely researched topic today. On the other hand, being able to recover the original speech from the noisy signal with minimal distortion is a challenge due to the difficulties in removing the background noise. Numerous factors in environmental noise environments can interfere with the signal. In this study, the performance of some discrete wavelets transform methods is experimentally analyzed using different wavelet filters. The analysis program was carried out in the MATLAB environment. As the input noise speech signal, speech sounds containing different environmental background noises (train, car, station, plane, etc.) were analyzed. During the tests, these noisy input signals were filtered out from the speech signal by wavelet analysis. The input noisy speech signal is decomposed into wavelet coefficients with different thresholding methods. The reconstructed speech was compared by measuring the signal-to-noise ratio (SNR) values between the noisy input signal and the smoothed output signals. The scientific contributions of the study include a detailed comparative analysis of the performances of various wavelet methods against different background environmental noises. © 2022 IEEE.Article Speech Enhancement using Maximal Overlap Discrete Wavelet Transform Method(2019) Özaydın, Selma; Alak, İman KhalilSignal denoising for non-stationary digital signals can be effectively succeeded by using discrete wavelet transform. Selecting of a suitable thresholding method is important to minimize the loss of useful signal information. This paper demonstrates the application of the maximal overlap wavelet transform (Modwt) technique in speech signal denoising. The analysis algorithm was performed on Matlab platform. In this algorithm, different kinds of input noisy speech signals having environmental background noises such as restaurant, car, street or station were tested. The noisy signals were filtered from the speech signal by thresholding of wavelet coefficients with threshold estimation methods known as sgtwolog, modwtsqtwolog, heursure, rigrsure and minimax. The performance of the Modwt in denoising process was evaluated by comparing signal-to noise ratio (SNR) and mean square error (MSE) results to those of wellknown threshold estimation methods. First, denoising effectiveness of a Modwt based threshold method was tested in different scenarios and very important improvements in denoising process were achieved by Modwt based scenarios. Next, the influence of the different wavelets families on Modwt based threshold estimation method was evaluated by experimental results. The results revealed that Modwt based method outperforms conventional threshold methods while providing nearly up to a %24 increase in SNR value.Article Comparative Analysis of Early Studies on Turkish Whistle Language and a Case Study on Test Conditions(2018) Özaydın, SelmaThis paper examines the early studies on Turkish Whistle Language and it argues that they have some controversial results. The study considers these issues need to be discussed and searched again in terms of linguistic and phonetic form. Unfortunately, there are few research studies on Turkish whistle language and most of them were performed nearly fifty years ago despite the fact that this language still has been used in Kuskoy region. Therefore, the findings of these early research studies could give valuable information to start to a new research study on the subject. The first scientific study on Turkish Whistle language was performed by a French scientist R.G. Busnel with his multidisciplinary research team in 1967. Some of this research’s results were published in the book. A Turkish scientist O. Baskan also participated in Busnel’s research group and published a paper on TWsL in 1968. However, some assertions such as people having a tendency to understand the Turkish whistle language with three vowels and three consonants have not been in the research results of R.G. Busnel. In addition, a Turkish scientist D. Aksan in Turkey had performed another research at Kuskoy region with his own team. Their test methods were different from the previous ones. This paper analyzes these research results on a comparative basis and presents the common and conflicted issues to discuss the uncertain points. The comparative evaluation of these past research studies aims to highlight the controversial position of the results on Turkish Whistle Language. In this scope, this paper opens a discussion about the selection of test conditions for an acoustic and linguistic analysis of the Turkish whistle language.Conference Object Evaluation of Acoustic Phonetic Properties of Turkish Whistle Language(2018) Özaydın, SelmaConference Object Citation - Scopus: 2Design of a Voice Activity Detection Algorithm Based on Logarithmic Signal Energy(Institute of Electrical and Electronics Engineers Inc., 2022) Ozaydin, S.This article presents a new method for calculating the signal energies of speech segments in voice activity detection algorithms. In the study, the μ-law signal compression method is adapted to calculate short-term signal energies. A simple voice activity detection (VAD) algorithm is designed to demonstrate the effectiveness of the proposed method. The same VAD algorithm was also run with two different conventional energy calculation formulas and the performance of each VAD was evaluated using time-domain short-time energy features. The G729 standard VAD algorithm was also used for performance comparison. During the test of the analyzed detectors, many kinds of input speech signals with various types of background environmental noise, such as restaurants, vehicles, and streets, were tested. Using the new energy calculation method, the VAD detector has improved detection accuracy compared to VAD detectors based on the other two energy methods and was able to effectively identify voice-active regions even in noisy conditions at low SNR levels. The results revealed that the VAD detector designed with the proposed new energy calculation formula outperforms traditional energy-based voice activity detection methods and provides noticeable increases in detection rate even under adverse conditions. © 2022 IEEE.Article Residual Lsf Vector Quantization Using Arma Prediction(2016) Özaydın, SelmaThe residual LSF vector quantization yields bit rate reduction in the vocoders. In this work, a residual LSF vector quantization obtained from Auto Regressive Moving Average (ARMA) prediction is proposed for designing codebooks at very low bit rates. This residual quantization method is applied to multi stage vector quantization method and codebooks are designed. For each codebook, the effectiveness and quality are investigated by calculating the spectral distortion and outliers. The proposed quantization method reduced the distortion without any additional complexity.Article Ecg Signal Denoising With Scilab(Ismail Saritas, 2023) Ahmad, I.; Özaydın, Selma; Ozaydin, S.; Çankaya Meslek YüksekokuluThis paper presents a study on de-noising electrocardiogram (ECG) signals using Scilab, an open-source software package known for its signal processing capabilities. ECG signals are often contaminated by various noise sources, which can reduce the accurate diagnosis and monitoring of heart health. In this work, digital signal processing methods such as Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters are used to effectively suppress noise while preserving the essential features of the ECG waveform. We explore main noise sources that commonly affect ECG recordings, such as baseline wandering noise, power-line interference, and muscle artifacts, and discuss their respective challenges. The de-noising methods has been extensively evaluated and demonstrated its ability to improve signal quality and diagnostic accuracy by eliminating noise artifacts. The results highlight Scilab's potential for de-noising ECG signals and its importance in improving patient care and biomedical signal processing applications. The efficacy of the de-noising methods is thoroughly evaluated through comparative analyses with other commonly used de-noising approaches. Experimental results demonstrate its superiority in preserving the QRS complex while efficiently eliminating noise artifacts, leading to more accurate and reliable diagnostic information. In conclusion, this paper presents a comprehensive study on de-noising ECG signals using Scilab, offering a valuable contribution to the field of biomedical signal processing. Researchers and practitioners in the domain of ECG signal processing can benefit from the insights and techniques presented herein to advance their studies and further applications. © 2023, Ismail Saritas. All rights reserved.Conference Object Citation - Scopus: 1An Isolated Word Speaker Recognition System(Institute of Electrical and Electronics Engineers Inc., 2017) Ozaydin, S.The paper presents a design of an isolated word speaker recognizer system by using the Hidden Markov Model. HTK toolkit is used as a design tool. The system is operated on a closed set of speakers and with a limited vocabulary of words. Digit utterances from one to ten with ten speakers (7 male, 3 female) are used as dataset in the system. It consists of isolated words that are separated by silences. Each speaker reads each word ten times. Six of them are used in training and the remaining are used in the test phase. The Mel cepstral coefficients are used in order to design the acoustic features and HMM models are constructed. A threshold calculation is performed for each speaker. After threshold adjustment, tests are performed for the performance evaluation and accuracy rates are calculated for each user. The system resulted in changing levels of recognition accuracy for each speaker and each word. © 2017 IEEE.
