基于土耳其语语音命令的伽玛倒谱系数国际象棋游戏
Turkish Voice Commands based Chess Game using Gammatone Cepstral Coefficients
摘要：
这项研究的目的是使行动能力有限的人能够实时的下象棋，并与周围的人一起玩游戏，而不会受到任何社会困扰或压力。对50人（23名男性和27名女性）进行了录音。在记录声音时，使用了每个人的29个单词，这些单词被确定为玩游戏所必需的。使用Mel频率系数（MFCC）和伽马倒谱系数（GTCC）鉴定方法。此外，k-NN，朴素贝叶斯和神经网络分类方法用于分类。采用了两种不同的分类程序，即基于个人的分类和一般分类。按人分类的执行率为75%至98%，而一般分类的执行率超过84%。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
