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Publication Type : Conference Paper
Publisher : 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015
Source : 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015, Institute of Electrical and Electronics Engineers Inc. (2015)
ISBN : 9781467373999
Keywords : Additive noise, Cepstral coefficients, Classification (of information), Cosine distance scoring, Individual systems, Mel-frequency cepstral coefficients, Robustness (control systems), Semantics, Signal to noise ratio, Speaker recognition evaluations, Speaker verification, Speaker verification system, Speech recognition, Support vector machine classifiers, Support vector machines, Vectors
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication, Mechanical Engineering
Year : 2015
Abstract : pCosine distance similarities with a set of reference speakers, cosine distance features (CDF), with a backend support vector machine classifier (CDF-SVM) have been explored in our earlier studies for improving the performance of speaker verification systems. Subsequently, we also investigated on its effectiveness in improving the noise robustness of speaker verification systems. In this work, we study how the performance of CDF-SVM systems can be further improved by weighting the feature vectors using latent semantic information (LSI) technique. We use mel frequency cepstral coefficients (MFCC), power normalized cepstral coefficients (PNCC), or delta spectral cepstral coefficients (DSCC) for deriving CDF. Experimental results on the female part of short2-short3 trials of NIST speaker recognition evaluation dataset show that the proposed weighted CDF-SVM system outperforms the baseline i-vector with cosine distance scoring (i-CDS), i-vector with a backend SVM classifier (i-SVM) and CDF-SVM systems. Finally, we fused the weighted CDF-SVM with i-CDS and the performance of the combined system was evaluated under different stationary and non-stationary additive noise test conditions. It was seen that the noise robustness of the fused weighted CDF-SVM+i-CDS system is significantly better than the individual systems and the fused CDF-SVM+i-CDS of our earlier work in both clean and noisy test environments except for the zero SNR level condition of certain noises. © 2015 IEEE./p
Cite this Research Publication : Dr. Santhosh Kumar C., George, K. K., Dr. K. I. Ramachandran, and Panda, A., “Weighted cosine distance features for speaker verification”, in 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015, 2015.