참고문헌
- J. Beh, R. H. Baran, and H. Ko, "Dual channel based speech enhancement using novelty filter for robust speech recognition in automobile environment," IEEE Trans. Consumer Electronics 52, 583-589 (2006). https://doi.org/10.1109/TCE.2006.1649683
- J. Beh and H. Ko, "Spectral subtraction using spectral harmonics for robust speech recognition in car environments," LNCS 2660, 1109-1116 (2003).
- L. R. Labiner and M. R. Sambur, "An algorithm for determining the endpoints for isolated utterance," Bell Syst. Tech. J. 54, 297-315 (1975). https://doi.org/10.1002/j.1538-7305.1975.tb02840.x
- L. R. Labiner and B. H. Juang, Fundamentals of Speech Recognition, (Prentice Hall, NJ, 1993).
- ITU-T, A Silence Compression Scheme for G.729 Optimized for Terminals Conforming to ITU-T V.70, (ITU-T Rec. G. 729, Annex B, 1996).
- J. G. Wilpon and L. R. Labiner, "Application of hidden Markov models to automatic speech endpoint detection," Comput. Speech Lang. 2, 321-341 (1987). https://doi.org/10.1016/0885-2308(87)90015-5
- E. Nemer, R. Goubran, and S. Mahmoud, "Robust voice activity detection using higher-order statistics in the LPC residual domain," IEEE Trans. Speech Audio Process. 9, 217-231 (2001). https://doi.org/10.1109/89.905996
- K. Li, M. N. S. Swamy, and M. O. Ahmad, "An improved voice activity detection using higher order statistics," IEEE Trans. Speech Audio Process. 13, 965-974 (2005). https://doi.org/10.1109/TSA.2005.851955
- B. F. Wu and K. C. Wang, "Robust endpoint detection algorithm based on the adaptive band-partitioning spectral entropy in adverse environments," IEEE Trans. Speech Audio Process. 13, 762-775 (2005). https://doi.org/10.1109/TSA.2005.851909
- Q. Li and A. Tsai, "A matched filter approach to endpoint detection for robust speaker verification," in Proc. IEEE Work. AIAT (1999).
- Q. Li, J. Zheng, A. Tsai, and Q. Zhou, "Robust endpoint detection and energy normalization for real-time speech and speaker recognition," IEEE Trans. Speech Audio Process. 10, 146-157 (2002). https://doi.org/10.1109/TSA.2002.1001979
- H. Ghaemmaghami, R. Vogt, S. Sridharan, and M. Mason, "Speech endpoint detection using gradient based edge detection techniques," in Proc. ICSPCS, 1-8 (2008).
- T. Fukuda, O. Ichikawa, and M. Nishimura, "Long-term spectro-temporal and static harmonic features for voice activity detection," IEEE J. STSP 4, 834-844 (2010).
- K. Ishizuka, T. Nakatani, and M. Fujimoto, "Noise robust front-end processing with voice activity detection based on periodic to aperiodic component ratio," Speech Communication 52, 41-60 (2010). https://doi.org/10.1016/j.specom.2009.08.003
- T. Kristjansson, S. Deligne, and P. Olsen, "Voicing features for robust speech detection," in Proc. Interspeech, 369-372 (2005).
- Q. Jo, J. Chang, J. Kim, and N. Kim, "Statistical modelbased voice activity detection using support vector machine," IET Signal Process. 3, 205-210 (2009). https://doi.org/10.1049/iet-spr.2008.0128
- Q. Jo, Y. Park, K. Lee, and J. Jang, "A support vector machine-based voice activity detection using effective feature vectors" (in Korean) J. Telecommunications Review 18, 362-370 (2008).
- N. C. Maddage, K. Wan, and C. Xu, Wang, "Singing voice detection using twice-iterated composite fourier transform," in Proc. IEEE ICME, 1347-1350 (2004).
- S. Gazor and W. Zhang, "A soft voice activity detector based on a Laplacian-Gaussian model," IEEE Trans. Speech Audio Process. 11, 498-505 (2003). https://doi.org/10.1109/TSA.2003.815518
- J. Sohn and W. Sung, "A Voice activity detector employing soft decision based noise spectrum adaptation," in Proc. IEEE ICASSP, 365-368 (1998).
피인용 문헌
- Performance Evaluation of Silence-Feature Normalization Model using Cepstrum Features of Noise Signals 2017, https://doi.org/10.1007/s11277-017-4645-x