Browsing by Author "Uslu, Baran"

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Design and Implementation of an Expressive Talking Mobile Robot: Toztorus
(Ieee, 2018) Tozan, Ozalp; Tora, Hakan; Uslu, Baran; Unal, Bulcnt; Ceylan, Ece; Computer Engineering; Airframe and Powerplant Maintenance
This 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.
Citation - WoS: 7
Hand Gesture Classification Using Inertial Based Sensors Via a Neural Network
(Ieee, 2017) Akan, Erhan; Tora, Hakan; Uslu, Baran; Airframe and Powerplant Maintenance; Department of Electrical & Electronics Engineering
In 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.
Higher Order Statistical Analysis of Turkish Phones
(Ieee, 2014) Tora, Hakan; Uslu, Baran; Airframe and Powerplant Maintenance
In 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.
Naturalness Analysis of the Speech Synthesized by a Tts Card
(Ieee, 2016) Tora, Hakan; Uslu, Baran; Airframe and Powerplant Maintenance
It 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.
Segmentation of Isolated Words Into Voiced-Unvoiced Sound Components by Kurtosis
(Ieee, 2015) Uslu, Baran; Tora, Hakan; Airframe and Powerplant Maintenance
This 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.
Citation - WoS: 1
THE USE OF CUMULANTS FOR VOICED-UNVOICED SEGMENTS IDENTIFICATION IN SPEECH SIGNALS
(Ieee, 2014) Uslu, Baran; Tora, Hakan; Airframe and Powerplant Maintenance
In 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.