Graduate School of Informatics

For further information please visit Graduate Awards.

Application deadline:10 May 2019

One Assistant Professor Position open in METU Cognitive Science until filled March 2019

Middle East Technical University Cognitive Science department seeks applicants for assistant professorship position (Dr. Öğretim Üyesi) in Cognitive Science. Eligible candidates must be Turkish citizens. Benefits (lodging, start up grants, kindergarten etc.) are potentially available if eligible and desired.

Candidates must hold a PhD in cognitive science or one of the fields in cognitive science, including computer science, computer engineering, linguistics, philosophy and psychology. Other candidates can be considered if they have a strong international research record in cognitive science.

Candidates must have a strong research record in modeling of large to massive data in an area within or closely related to cognitive science.  Duties include publishing high quality research, teaching two courses per term, advising MSc students in the department for thesis and graduation projects, advising PhD students if there is track record of having advised MSc theses earlier, participation in department’s activities and committees, seeking grant applications for research in cognitive science nationwide and internationally, and efforts to establish laboratories for research.  The department has granted 131 MSc theses and 28 PhDs in the last twenty years.

A search committee will evaluate the applications; final appointment approval pending on university and YÖK decision. For consideration please contact cogs@metu.edu.tr with research portfolio and cover letter.

Graduate School of Informatics /Information Systems

In partial fulfillment of the requirements for the degree of Master of YASER YURTCAN will defend his thesis.

Title: Performance Evaluation of Real-Time Noisy Speech Recognition For Mobile Devices

Date: 12th February 2019

Time: 10:30 AM

Place: A-212

Abstract: Communication is important for people. There are many available communication methods. One of the most effective methods is through the use of speech. People can comfortably express their feelings and thoughts by using speech. However, some people may have a hearing problem. Furthermore, understanding spoken words in a noisy environment could be a challenge even for healthy people. Speech recognition systems enable real-time speech to text conversion. They mainly involve capturing of the sound waves and converting them into meaningful texts.

The use of speech recognition on mobile devices has been possible with the development of cloud systems. However, delivering a robust and low error rate speech recognition system in a noisy environment still is a major problem. In this study, different speech samples have been recorded using a compact microphone array in noisy environments and a data set has been created by processing them through a real-time noise cancellation algorithm. A portable design of a mobile system with noise cancellation hardware and software was proposed to convert spoken words to a meaningful text.

Comprehensive tests were performed on several clean, noisy and denoised speech samples to measure the speech recognition performance of different cloud systems, noise robustness of the proposed system, the effect of gender on the speech recognition performance, and the performance improvement. The experimental results show that the proposed system provides good performance even in a noisy environment. It is also inferred from the results that in order to apply speech recognition using cloud based systems on mobile devices, the noise level has to be low or real-time noise cancellation algorithms are needed. The proposed system improves speech recognition accuracy in noisy environments. Thus, the achieved performance and portable design together enable the system to be used in daily life.

Synopsis: The aim of this study is to improve noisy speech recognition performance on mobile
devices. This study approaches the problem as a system design issue and integrates
suitable hardware and software components to achieve the desired results. The proposed system is described in detail, explain the specifications of the noise cancellation algorithm used, state reasons of selected transfer media and describe an application of speech recognition. Detailed results are provided and discussed. Therefore, improving the existing noise cancellation or speech recognition algorithms is beyond the scope of this thesis.

Cybersecurity Department Applications of Transfer from MSc Non-Thesis to MScThesis are evaluated  and the names of the candidates who are eligible for the transfer to the Thesis Master program are given below.

2025-2026 Spring Semester Course Programs

BIN / Bioinformatics - Thesis Courses Section Information
COGS / Cognitive Science - Thesis Courses Section Information
IS/ Information Systems - Thesis Courses Section Information
MIN / Medical Informatics - Thesis Courses Section Information
DI / Data Informatics - Thesis Courses Section Information
MMI / Multimedia Informatics - Thesis Courses Section Information
CSEC / Cybersecurity - Thesis Courses Section Information