Browsing by Author "Uslu,B."
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Conference Object Citation Count: 0Design and Implementation of an Expressive Talking Mobile Robot: TozTorUs(Institute of Electrical and Electronics Engineers Inc., 2018) Tozan, Özalp; Tora, Hakan; Uslu,B.; Una,B.; Ceylan,E.; Computer Engineering; Airframe and Powerplant MaintenanceThis paper is about a brand new robot and all its development stages from the design to the show time. As an undergraduate research project (the LAP program at Atilim University), the robot TozTorUs is the outcome of the dense efforts of a team. With the sensors equipped, it navigates autonomously in the environment in which it is located by avoiding the obstacles. It can understand your questions and answer them using Google's speech technologies. Although it is not a humanoid robot, with eyes and mouth simulator LED displays, it is as friendly as a human. We can also control TozTorUs using a mobile phone. Apart from these, it is able to adjust its height with respect to the visitor's, thus allowing it to make an eye contact with the person. Although TozTorUs is designed for welcoming, it may also be employed for consulting, security and elderly assistance. © 2018 IEEE.Conference Object Citation Count: 0Design and Implementation of an Expressive Talking Mobile Robot: TozTorUs(Institute of Electrical and Electronics Engineers Inc., 2018) Tozan, Özalp; Tora, Hakan; Uslu,B.; Una,B.; Ceylan,E.; Computer Engineering; Airframe and Powerplant MaintenanceThis paper is about a brand new robot and all its development stages from the design to the show time. As an undergraduate research project (the LAP program at Atilim University), the robot TozTorUs is the outcome of the dense efforts of a team. With the sensors equipped, it navigates autonomously in the environment in which it is located by avoiding the obstacles. It can understand your questions and answer them using Google's speech technologies. Although it is not a humanoid robot, with eyes and mouth simulator LED displays, it is as friendly as a human. We can also control TozTorUs using a mobile phone. Apart from these, it is able to adjust its height with respect to the visitor's, thus allowing it to make an eye contact with the person. Although TozTorUs is designed for welcoming, it may also be employed for consulting, security and elderly assistance. © 2018 IEEE.Conference Object Citation Count: 9Hand gesture classification using inertial based sensors via a neural network(Institute of Electrical and Electronics Engineers Inc., 2017) Akan, Erhan; Tora, Hakan; Uslu,B.; Airframe and Powerplant Maintenance; Department of Electrical & Electronics EngineeringIn this study, a mobile phone equipped with four types of sensors namely, accelerometer, gyroscope, magnetometer and orientation, is used for gesture classification. Without feature selection, the raw data from the sensor outputs are processed and fed into a Multi-Layer Perceptron classifier for recognition. The user independent, single user dependent and multiple user dependent cases are all examined. Accuracy values of 91.66% for single user dependent case, 87.48% for multiple user dependent case and 60% for the user independent case are obtained. In addition, performance of each sensor is assessed separately and the highest performance is achieved with the orientation sensor. © 2017 IEEE.Conference Object Citation Count: 1Higher order statistical analysis of Turkish phones;(IEEE Computer Society, 2014) Tora, Hakan; Uslu,B.; Airframe and Powerplant MaintenanceIn 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. © 2014 IEEE.Conference Object Citation Count: 0Segmentation of isolated words into voiced-unvoiced sound components by kurtosis;(Institute of Electrical and Electronics Engineers Inc., 2015) Tora, Hakan; Tora,H.; 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 Citation Count: 2The use of cumulants for voiced-unvoiced segments identification in speech signals;(IEEE Computer Society, 2014) Tora, Hakan; Tora,H.; Airframe and Powerplant MaintenanceIn 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. © 2014 IEEE.Article Citation Count: 0Vowel classification based on waveform shapes(ASTES Publishers, 2019) Tora, Hakan; Karacor,G.; Uslu,B.; Airframe and Powerplant MaintenanceVowel classification is an essential part of speech recognition. In classical studies, this problem is mostly handled by using spectral domain features. In this study, a novel approach is proposed for vowel classification based on the visual features of speech waveforms. In sound vocalizing, the position of certain organs of the human vocal system such as tongue, lips and jaw is very effective on the waveform shapes of the produced sound. The motivation to employ visual features instead of classical frequency domain features is its potential usage in specific applications like language education. Even though this study is confined to Turkish vowels, the developed method can be applied to other languages as well since the shapes of the vowels show similar patterns. Turkish vowels are grouped into five categories. For each vowel group, a time domain speech waveform with an interval of two pitch periods is handled as an image. A series of morphological operations is performed on this speech waveform image to obtain the geometric characteristics representing the shape of each class. The extracted visual features are then fed into three different classifiers. The classification performances of these features are compared with classical methods. It is observed that the proposed visual features achieve promising classification rates. © 2019 Advances in Science, Technology and Engineering Systems.All rights reserved.