Speaker Recognition and Verification is becoming one of the widely used forms of biometric authentication in today’s scenario where remembering strings of textual passwords and numbers are becoming a hassle. Authentication of users using voice offers many advantages and easy to use techniques. In this paper a comparison is drawn among the most commonly used feature extraction techniques in Speaker Recognition and Verification. Extracting useful and unique features from the user’s voice forms the backbone of an efficient Speaker Recognition System. Here, the most commonly used methods for Feature Extraction viz. MFCC (Mel Frequency Cepstral Coefficient), LPC (Linear Predictive Coefficient), PLP (Perceptual Linear Prediction) are discussed, compared and an attempt is made to deduce which one performs best.
목차
Abstract 1. Introduction 2. Steps in Speaker Recognition 3. Feature Extraction 4. MFCC (Mel Frequency Cepstral Coefficient) 4.1. Framing 4.2. Fast Fourier Transform 4.3. Mel Scale Filtering 4.4. Logarithm 4.5. Discrete Cosine Transform 4.6. Delta Energy and Spectrum 5. LPC (Linear Predictive Coding) 5.1. Preemphasis 5.2. Frame Blocking 5.3. Windowing 5.4. Autocorrelation Analysis 5.5. LPC Analysis 5.6. Conversion of LPC Parameters to Cepstral Coefficients 6. PLP (Perceptual Linear Prediction) 6.1. Windowing 6.2. Calculation of Power Spectrum 6.3. Application of Frequency Warping into Bark Scale 6.4. Equal Loudness Pre Emphasis 6.5. Intensity Loudness 6.6. Linear Prediction 6.7. Cepstrum Computation 7. Tabular Comparison of MFCC, LPC and PLP 8. Conclusion References
키워드
Speaker RecognitionSpeaker VerificationMFCCMel Frequency Cepstral CoefficientLPCLinear Predictive CoefficientPLPPerceptual Linear Prediction
저자
Jaison Joshy [ Department of Computer Science and Engineering, National Institute of Technology, Arunachal Pradesh, India ]
Koj Sambyo [ Department of Computer Science and Engineering, National Institute of Technology, Arunachal Pradesh, India ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9 No.11