Turkish Voice Commands based Chess Game using Gammatone Cepstral Coefficients
This enables people with mobility impairments to play chess in real-time without social stress, but it is incremental as it applies existing methods to a new language and domain.
The study developed a Turkish voice command system for chess to assist individuals with limited mobility, achieving performance rates of 75-98% in person-based classification and over 84% in general classification.
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.