计算机技术与发展
計算機技術與髮展
계산궤기술여발전
COMPUTER TECHNOLOGY AND DEVELOPMENT
2015年
2期
140-143
,共4页
汽车声音识别%梅尔倒谱系数%自相关函数%高斯混合模型
汽車聲音識彆%梅爾倒譜繫數%自相關函數%高斯混閤模型
기차성음식별%매이도보계수%자상관함수%고사혼합모형
vehicle audio recognition%MFCC%ACF%Gaussian mixture model
汽车声音识别是汽车声源定位等研究的基础，对交通事故鉴定、犯罪举证和犯罪现场还原等具有重要意义。现有汽车声音识别算法存在算法复杂度高和识别率相对较低等问题。针对现行问题，将以梅尔倒谱系数( MFCC)特征与自相关函数(ACF)方差作为混合特征的汽车声音识别算法应用到汽车声音识别系统中。该算法使用高斯混合模型(GMM)进行汽车声音建模和识别，获得比MFCC特征及其一阶差分特征组成的混合特征更好的识别效果。并通过仿真实验证明了该算法的有效性。
汽車聲音識彆是汽車聲源定位等研究的基礎，對交通事故鑒定、犯罪舉證和犯罪現場還原等具有重要意義。現有汽車聲音識彆算法存在算法複雜度高和識彆率相對較低等問題。針對現行問題，將以梅爾倒譜繫數( MFCC)特徵與自相關函數(ACF)方差作為混閤特徵的汽車聲音識彆算法應用到汽車聲音識彆繫統中。該算法使用高斯混閤模型(GMM)進行汽車聲音建模和識彆，穫得比MFCC特徵及其一階差分特徵組成的混閤特徵更好的識彆效果。併通過倣真實驗證明瞭該算法的有效性。
기차성음식별시기차성원정위등연구적기출，대교통사고감정、범죄거증화범죄현장환원등구유중요의의。현유기차성음식별산법존재산법복잡도고화식별솔상대교저등문제。침대현행문제，장이매이도보계수( MFCC)특정여자상관함수(ACF)방차작위혼합특정적기차성음식별산법응용도기차성음식별계통중。해산법사용고사혼합모형(GMM)진행기차성음건모화식별，획득비MFCC특정급기일계차분특정조성적혼합특정경호적식별효과。병통과방진실험증명료해산법적유효성。
Vehicle audio recognition is the foundation of vehicle sound source localization and other automotive research,it is very impor-tant for traffic accidents identification,crime scene evidence and crime reduction. The problem of high computational complexity and rela-tively low recognition rate has existed in current vehicle audio recognition. Concerning those problems above,the vehicle recognition algo-rithm taking Mel-Frequency Cepstrum Coefficients and improved Auto-Correlation Function as hybrid feature is applied in the vehicle audio recognition system. Modeling and classifying by the Gaussian Mixture Model,this feature vector outperforms MFCC and Differenti-al MFCC features in recognition. The simulation results prove the effectiveness of the proposed algorithm.
