References
- H. K. Kim, and R. C. Cox, 'Evaluation of robust speech recognition algorithms for distributed speech recognition in a noisy automobile environment,' Proc. ICSLP 2002, 233-236, Sept. 2002
- C.-P. Chen, K. Filali, amd J. F. Bilmes, 'Frontend postprocessing and backend model enhancement on the Aurora 2.0/3.0 databases,' Proc. ICSLP 2002, 241-244, Sept. 2002
- M. Marzinzik, and B. Kollmeier, 'Speech pause detection for noise spectrum estimation by tracking power envelope dynamics,' IEEE Trans. Speech and Audio Processing, 10 (2). 109-110, Feb. 2002 https://doi.org/10.1109/89.985548
- W.-H. Shin, B.-S. Lee, Y.-K. Lee. and J.-S. Lee, 'Speech/Non-speech classification using multiple features for robust endpoint detection'" Proc. ICASSP 2000. Ill. 1399-IIl. 1402, 2000
- B. Kotnik, Z. Kacic, and B. Horvat, 'A computational efficient real time noise robust speech recognition based on improved spectral subtraction method.' Proc. EUROSPEECH 2001, 1123-1126, 2001
- L. Karray, and A. Martin, 'Towards improving speech detection robustness for speech recognition in adverse conditions'" Speech Communication. 40 (3), 261-276, May 2003 https://doi.org/10.1016/S0167-6393(02)00066-3
- R. Martin, 'Spectral subtraction based on minimum statistics.' Signal Processing VII, Theories and Applications. Proc. EUSIPCO-94, 1182-1185. 1994
- N. W. D. Evans, and J. S. Mason, 'Noise estimation without explicit speech, non-speech detection: A comparison of mean, modal and median based approaches,' Proc. EUROSPEECH 2001. 893-896, 2001
- R. E. Schapire, and Y. Singer, "Improved boosting algorithms using confidence -rated predictions,' Machine Learning, 37 (3), 297-336, 1999 https://doi.org/10.1023/A:1007614523901
- Y. Freund, and R. E. Schapire, 'A decision-theoretic generalization of on-line learning and an application to boosting,' Journal of Computer and System Sciences, 55 (1), 119-139, 1997 https://doi.org/10.1006/jcss.1997.1504
- A. Benyassine, E. Shlomot, and H.-Y. Suo 'ITU-T Recommendation G.729 Annex B: A silent compression scheme for use with G.729 optimized for V.70 digital simultaneous voice and data applications,' IEEE Communications Magazine, 64-73, Sept. 1997
- H. G. Hirsch. and D. Pearce, 'The AURORA experimental framework for the performance evaluations of speech recognition systems under noisy conditions,' ISCA ITRW ASR2000 Automatic Speech Recognition: Challenges for the Next Millennium, Paris, France, Sept. 18-20, 2000
- A. Acero, Acoustical and Environmental Robustness in Automatic Speech Recognition, Kluwer Academic Publishers, Boston, 1993