Ensar Kalayci’s scientific contributions

Blindfold chess is of particular interest in the research of the memory structure and limits of the human brain. In blindfold chess, the player cannot see the board so the player visualizes the situation and make his moves aloud. In this study, the first step of recognition of voice commands for blindfold chess, word-based determination, and classification of chess figure vocalizations have been emphasized. Mel frequency coefficients and mel spectrograms have been used as the feature vector for audio data. The classification of these vectors has been made by using artificial neural networks. As a result of the tests, 99% success has been obtained in noisy environments.