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Conference Object Higher Order Statistical Analysis of Turkish Phones(Ieee, 2014) Tora, Hakan; Uslu, BaranIn this study, histograms of Turkish phones were examined using higher order cumulants. As is known, phones constituting a language, are composed of letters as vowels and consonants. These letters can also be grouped as voiced and unvoiced phones. It is observed that unvoiced letters show a Gaussian-like distribution and result in small values of skewness and kurtosis. On the other hand, vowels and voiced consonants lead to a non-Gaussian distribution. Voiced and unvoiced phones are related with their skewness and kurtosis values. It is empirically shown that higher order cumulants are likely to be a feature in describing Turkish phones.Conference Object Naturalness Analysis of the Speech Synthesized by a Tts Card(Ieee, 2016) Tora, Hakan; Uslu, BaranIt is known that the performance of a developed text-to-speech (TTS) synthesis system is assessed by subjective tests. These assessments are usually based on the intelligibility and naturalness of the synthesized speech. In this study, an investigation on relating these subjective test results, thus the naturalness of the synthesized speech, to which acoustic features is accomplished. Consequently the features which will increase the performance while synthesizing the speech are determined. Our work is focused especially on the pitch frequency and energy parameters.Conference Object Citation - WoS: 1THE USE OF CUMULANTS FOR VOICED-UNVOICED SEGMENTS IDENTIFICATION IN SPEECH SIGNALS(Ieee, 2014) Uslu, Baran; Tora, HakanIn this study, voiced-unvoiced classification performance of Turkish sounds using skewness and kurtosis is examined. The analyses show that higher order cumulants can be employed as a feature in voiced-unvoiced classification that is vital in speech processing applications. Furthermore, it has been shown that cumulants are also useful for identifying voiced and unvoiced segments in noisy speech signals.Conference Object Segmentation of Isolated Words Into Voiced-Unvoiced Sound Components by Kurtosis;(Institute of Electrical and Electronics Engineers Inc., 2015) Uslu,B.; Tora, Hakan; Tora,H.; Tora, Hakan; Airframe and Powerplant Maintenance; Airframe and Powerplant MaintenanceThis study presents a new approach to the segmentation of isolated words into their voiced/ unvoiced parts. It is well known that voiced/ unvoiced discrimination has an important role in speech synthesis and coding applications. The offered method makes this discrimination using the kurtosis values of the words. The performance of the proposed approach was tested on Turkish digit recordings from zero to nine. It has been observed that this approach segments the parts successfully in not only clean speech but also in noisy speech. © 2015 IEEE.Conference Object Segmentation of Isolated Words Into Voiced-Unvoiced Sound Components by Kurtosis(Ieee, 2015) Uslu, Baran; Tora, HakanThis study presents a new approach to the segmentation of isolated words into their voiced/unvoiced parts. It is well known that voiced/unvoiced discrimination has an important role in speech synthesis and coding applications. The offered method makes this discrimination using the kurtosis values of the words. The performance of the proposed approach was tested on Turkish digit recordings from zero to nine. It has been observed that this approach segments the parts successfully in not only clean speech but also in noisy speech.Conference Object Citation - WoS: 1Recognition of Hand-Sketched Digital Logic Gates(Ieee, 2015) Gul, Nuray; Tora, HakanHand-Sketched circuit recognition is a very useful tool in engineering area. Because most of the engineers prefer to design their circuits on the paper firstly. So, this can cause time wasting and some mistakes. In this study, which is based on the solving these kinds of problems, classification and recognition of the handwritten digital logic gates according to their complex and scalar FDs (Fourier Descriptors) is presented. Test results are obtained as 84.3 % accuracy rate for complex FDs, 98.6 % for scalar FDs. Then these results are compared and decided the optimum FDs type for this study.Article Yalıtık Sözcüklü Bir Türkçe Konuşma Tanıma Sisteminin Yapay Veri Artırımı ile Tasarımı ve Gerçekleştirimi(2020) Uslu, İbrahim Baran; Tora, Hakan; Sümer, Emre; Türker, MustafaBu çalışmada toplamda doksan iki adet sesli komuttan oluşan bir yalıtık sözcüklü Türkçe konuşmatanıma sistemi tasarlanmış ve gerçekleştirilmiştir. Sistem, destek vektör makinesi (SVM) tabanlı olup,eğitimde kullanılan veri kümesi kaydedilen konuşmaların yapay olarak çeşitlendirilip artırılmasıyla eldeedilmiştir. Farklı yapay veri oranlarının tanıma başarımı üzerindeki etkisi incelenmiştir. Akustik öznitelikolarak, mel frekansı kepstral katsayıları (MFCC) kullanılmıştır. Ayrıca, ses aktivitesi tespitinin ve MFCCkatsayılarının tanıma başarımına etkileri de irdelenmiştir. Sonuçta doksan iki yalıtık komut için ortalama%92.6’lık doğrulukla çalışan bir konuşma tanıma sistemi geliştirilmiştirConference Object An Approach for Perceptual Similarity Detection Between Audios Independent of Genre Via Metadata Extraction and Correlation(Ieee, 2007) Komsu, Fatma; Tora, Hakan; Oeztoprak, Kasim; Tora, Hakan; Tora, Hakan; Airframe and Powerplant Maintenance; Airframe and Powerplant MaintenanceThis study presents an approach for perceptual similarity detection between audios independent of genre. The study is formed of three phases; signal pre-processing as the first phase, metadata extraction via various perceptually compatible features as the second phase, and correlation methodology for similarity identification as the third phase. The performance and relative importance of the selected features for perceptual similarity analysis are presented, as testing results. Moreover, relative importance of preprocessing is introduced. Using the proposed methodology, perceptual similarity detection between genre independent audios is achieved with a 96.85% performance. Contribution highly lies on the independency of genre.Conference Object Performance Evaluation of Self Organizing Neural Networks for Clustering in Esm Systems(Ieee, 2014) Gencol, Kenan; Tora, HakanElectronic Support Measures (ESM) system is an important function of electronic warfare which provides the real time projection of radar activities. Such systems may encounter with very high density pulse sequences and it is the main task of an ESM system to deinterleave these mixed pulse trains with high accuracy and minimum computation time. These systems heavily depend on time of arrival analysis and need efficient clustering algorithms to assist deinterleaving process in modern evolving environments. On the other hand, self organizing neural networks stand very promising for this type of radar pulse clustering. In this study, performances of self organizing neural networks that meet such clustering criteria are evaluated in detail and the results are presented.Conference Object Citation - WoS: 1Lip Shape Based Emotion Identification(Ieee, 2016) Gul, Nuray; Tora, HakanEmotion recognition systems have an important role to play in the human-computer interactive applications (HCI). These systems are using facial features of face images and they are verifying or identifying the emotions. In this study, emotion identification algorithms are improved by using just mouth region features of a face. Region of interest (mouth region) is detected by Viola-Jones algorithms from video frames which are including different emotional face expressions. Outer boundaries of lip shapes are extracted by manually and calculated the scalar Fourier Descriptors (FDs) of the boundaries. Classification and recognition of the emotions is presented according to scalar FDs of lip contours. Test results are obtained as 93.9 % accuracy rate for scalar FDs.
