CAJ | 학술논문

目的利用双门限法、Mel频率倒普系数(MFCC)法及矢量量化(VQ)法的语音识别技术对咳嗽声音进行自动识别.方法在安静环境下,对5例健康成年人和15例咳嗽患者的非咳嗽和咳嗽声音进行录音,分别随机分为训练样本和测试样本.训练样本用于生成咳嗽识别软件的码本,并用该码本对测试样本进行自动识别分析.同时与人工识别的结果进行对比,计算敏感性、特异性,记录两种方法的识别时间.结果用于码本生成的咳嗽声音和非咳嗽声音均为200次,测试样本的咳嗽和非咳嗽声音分别为375次和125次.人工识别和通过码本自动识别测试样本的时间分别为33 min 18 s和1min 35 s;码本自动识别咳嗽声音的敏感性和特异性分别为98.93%和100%.结论基于VQ的双门限法及MFCC法可用于咳嗽声音的自动识别.
목적 이용쌍문한법、Mel빈솔도보계수(MFCC)법급시량양화(VQ)법적어음식별기술대해수성음진행자동식별.방법 재안정배경하,대5례건강성년인화15례해수환자적비해수화해수성음진행록음,분별수궤분위훈련양본화측시양본.훈련양본용우생성해수식별연건적마본,병용해마본대측시양본진행자동식별분석.동시여인공식별적결과진행대비,계산민감성、특이성,기록량충방법적식별시간.결과 용우마본생성적해수성음화비해수성음균위200차,측시양본적해수화비해수성음분별위375차화125차.인공식별화통과마본자동식별측시양본적시간분별위33 min 18 s화1min 35 s;마본자동식별해수성음적민감성화특이성분별위98.93%화100%.결론 기우VQ적쌍문한법급MFCC법가용우해수성음적자동식별.
Objective To investigate the feasibility of speech recognition technologies including double threshold method, Mel frequency cepstral coefficient (MFCC) and vector quantization (VQ) in automatic recognition of cough sounds. Methods Five healthy adults and 15 patients with cough were recruited for recording of both non- cough and cough sounds in a quiet environment. The records were randomized into training and testing samples. The training samples were used to generate the code book for cough recognition software, which was then used to recognize and analyze the testing samples automatically.The sensitivity and specificity of recognition were calculated by comparison with outcomes from human ear recognition. The recognition time in two approaches was recorded. Results Two hundred cough and 200 noncough sound samples were used to generate the code book for cough recognition software, while 375 cough sound samples and 125 non-cough sound samples were used as the testing samples. The recognition time of the testing samples needed was 33 minutes and 18 seconds by human ear recognition vs 1 minute and 35seconds by code book-based automatic recognition. In addition, the sensitivity and specificity in code bookbased automatic recognition of the cough sound were 98.93% and 100% respectively. Conclusion The double threshold method based on VQ and MFCC appears feasible in automatic recognition of cough sounds.