Robust speaker recognition based on filtering in autocorrelation domain and sub-band feature recombination

Pattern Recognition Letters

Volumn 31, Issue 7, 2010, Pages 593-599

  Kim, Sungtak ^a   Ji, Miyoung ^a   Kim, Hoirin ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Hybrid feature representation; Multi streaming feature extraction; Relative autocorrelation sequence mel frequency cepstral coefficients; Sub band feature recombination; Temporal filtering

Indexed keywords

HYBRID FEATURE REPRESENTATION; HYBRID FEATURES; MEL-FREQUENCY CEPSTRAL COEFFICIENTS; RELATIVE AUTOCORRELATION SEQUENCE; SUB-BANDS; TEMPORAL FILTERING;

CORRELATION DETECTORS; DATABASE SYSTEMS; LOUDSPEAKERS; SPEECH RECOGNITION;

FEATURE EXTRACTION;

EID: 77949271463     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2009.12.013     Document Type: Article

References (17)

1. Auckenthaler R., Carey M., and Lloyd-Thomas H. Score normalization for text-independent speaker verification systems. Digital Signal Process. 10 (2000) 42-54
2. Barras, C., Gauvain, J., 2003. Feature and score normalization for speaker verification of cellular data. In: Proc. ICASSP, pp. 49-52.
3. Drygajlo, A., El-Maliki, M., 1998. Speaker verification in noisy environments with combined spectral subtraction and missing feature theory. In: Proc. ICASSP, pp. 121-124.
4. JiQing, H., Lei, Z., Chengfa, W., 2000. An environment adaptation method for robust speech recognition. In: Proc. ICSP, pp. 726-729.
5. Kim S., Ji M., Suh Y., and Kim H. Noise robust speaker identification using sub-band weighting in multi-band approach. IEICE Trans. Inform. Systems E90-D 12 (2007) 2110-2114
6. Kim S., Ji M., and Kim H. Noise-robust speaker recognition using subband likelihoods and reliable-feature selection. ETRI J. 30 1 (2008) 89-100
7. Mak B. A mathematical relationship between full-band and multiband mel-frequency cepstral coefficients. IEEE Signal Process. Lett. 9 8 (2002) 241-244
8. Pearce, D., Hirsch, H., 2000. The Aurora experimental framework for the performance evaluation of speech recognition systems under noise conditions. In: Proc. ICSLP, pp. 29-32.
9. Ramos-Castro D., Fierrez-Aquilar J., Gonzalez-Rodriquez J., and Ortega-Garcia J. Speaker verification using speaker- and test-dependent fast score normalization. Pattern Recognition Lett. 28 (2007) 90-98
10. Reynold D. Large population speaker identification using clean and telephone speech. IEEE Signal Process. Lett. 2 3 (1995) 46-48
11. Reynold D., and Rose R.C. Robust text-independent speaker identification using gaussian mixture models. IEEE Trans. Speech Audio Process. 3 1 (1995) 72-83
12. Reynolds D., Quatieri T., and Dunn R. Speaker verification using adapted Gaussian mixture models. Digital Signal Process. 10 (2000) 19-41
13. Shao, Y., Wang, D., 2008. Robust speaker identification using auditory features and computational auditory scene analysis. In: Proc. ICASSP, pp. 1589-1692.
14. Shao, Y., Srinivasan, S., Wang, D., 2007. Incorporating auditory feature uncertainties in robust speaker identification. In: Proc. ICASSP, pp. 227-280.
15. Yiu, K., Mak, M., Kung, S., 2003. Environment adaptation for robust speaker verification. In: Proc. EUROSPEECH, pp. 2973-2976.
16. Yuo K.-H., and Wang H.C. Robust features for noisy speech recognition based on temporal trajectory filtering of short-time autocorrelation sequences. Speech Comm. 28 (1999) 13-24
17. Yuo K.-H., Hwang T.-H., and Wang H.-C. Combination of autocorrelation-based features and projection measure technique for speaker identification. IEEE Trans. Speech Audio Process. 13 4 (2005) 565-574