  This study was carried out to enable individuals with limited mobility skills
to play chess in real time and to play games with the individuals around them
without being under any social distress or stress. Voice recordings were taken
from 50 people (23 men and 27 women). While recording the sound, 29 words from
each person were used which are determined as necessary for playing the game.
Mel Frequency Coefficients (MFCC) and Gammatone Cepstral Coefficients (GTCC)
qualification methods were used. In addition, k-NN, Naive Bayes and Neural
Network classification methods were used for classification. Two different
classification procedures were applied, namely, person-based and general. While
the performance rate in person-based classification ranged from 75% to 98%, a
performance over 84% was achieved in general classification.
