The work reported in thesis investigates direction-of-arrival estimation methods for sound sources and proposes novel method called HiGRID and its extensions with DPD test and EB-MUSIC. Proposed methods are based on spherical harmonic decomposition and rigid spherical microphone arrays enables trivial calculation of spherical harmonic decomposition of sound fields. Evaluation of proposed methods are presented in terms of direction-of-arrival estimation errors.

Date: 26.07.2019 Place: A-212

Artificial reverberators provide a computationally viable alternative to full-scale room acoustics simulation methods for games and extended reality applications. Scattering delay network (SDN) is a relatively recent artificial reverberator that allows direct parametric control over the geometry of a simulated rectangular enclosure. We propose a new model called coupled volume scattering delay networks (CV-SDN) which extends the classic SDN structure for enclosures coupled via an aperture. The extension allows independent control of acoustical properties of volumes and the size of the connecting aperture. The utility of the proposed method is demonstrated by the energy decay curves obtained from impulse responses.

Date: 26.07.2019 Place: A-212

Video games are a great medium for storytelling. This thesis proposes a game development framework to help developers create role-playing games in a much easier and quicker fashion. With its modular structure, the proposed framework offers developers a highly scalable game development environment.

Date: 23.07.2019 10:00 Place: Computer Engineering Building A-105

Simply put cross-age effect or own-age bias is the phenomenon that when guessing the age of individuals from their faces, it is claimed that the age of the individual who is guessing the facial age effects the guessing process and the effect is towards to the age of the one who is guessing. In our study; the phenomenon is investigated in humans to observe if such effect exists, then it is tested if the error could be reduced via utilizing convolutional neural networks on face images and classify the face images with respect to their ages.

Date: 27.06.2019 16:30 Place: A-212

The study deals with the emotion recognition problem in Turkish single word pronunciations through the image recognition perspective. The CNN approach allowed us to use spectrograms as the training material. The resulting model has a feasible predictive power and shares trends with the human judges: it is robust to the changes in the sound signal at higher frequencies and generally performed better than the judges except for the 500-8000 hertz band where the human judges did not lose any significant predictive power. The model proved to be a feasible explanation of human assessment of emotions by failing at 500-8000 hertz band where the humans remained robust.

Date: 27.06.2019 13:30   Place: A-108