CAJ | 학술논문

现有的基于脚步声的身份识别研究方法均采用语音声学参数作为特征，例如梅尔倒谱系数、频谱包络相似度等，这类方法的缺点是对于同一人在不同鞋类和不同地板上的脚步声识别有很大的约束性和限制性，对不同的发声机制较为敏感。提出一种新的步声特征提取方法，用步声持续时间与步声间隔时间作为识别特征，最后使用k-nn算法做识别测试。实验结果表明，该方法对于脚步声的身份识别是有效的，对于不同发声机制下的脚步声有良好的适用性。
현유적기우각보성적신빈식별연구방법균채용어음성학삼수작위특정，례여매이도보계수、빈보포락상사도등，저류방법적결점시대우동일인재불동혜류화불동지판상적각보성식별유흔대적약속성화한제성，대불동적발성궤제교위민감。제출일충신적보성특정제취방법，용보성지속시간여보성간격시간작위식별특정，최후사용k-nn산법주식별측시。실험결과표명，해방법대우각보성적신빈식별시유효적，대우불동발성궤제하적각보성유량호적괄용성。
All existing footstep-based personal identification research methods take acoustics parameters as features,for instance, Mel-Frequency Cepstral Coefficients (MFCC ) and spectrum envelope similarity degree etc.Their common shortcomings are the severe constrain and limitation at recognizing the footsteps of one person with different shoes or on different floors since they are sensitive to different acoustic mechanisms.The article proposes a novel footstep feature extraction method,which takes footstep duration and interval lengths as recognizable features and finally uses k-nn algorithm for recognition test.Experiment results elaborate that the method is effective at footstep personal identification while it is well adaptive to footsteps under different acoustic mechanisms.