Unvoiced Speech Segregation From Nonspeech Interference via CASA and Spectral Subtraction

IEEE Transactions on Audio, Speech and Language Processing

Volumn 19, Issue 6, 2011, Pages 1600-1609

  Hu, Ke ^a   Wang, DeLiang ^a  

^a The Ohio State University   (United States)

Author keywords

Bayesian classification; computational auditory scene analysis (CASA); nonspeech interference; spectral subtraction; unvoiced speech segregation

Indexed keywords

EID: 85008054377     PISSN: 15587916     EISSN: 15587924     Source Type: Journal    
DOI: 10.1109/TASL.2010.2093893     Document Type: Article

References (37)

1. J. B. Allen, Articulation and Intelligibility. San Rafael, CA: Morgan & Claypool, 2005.
2. M. Berouti, R. Schwartz, and J. Makhoul, “Enhancement of speech corrupted by acoustic noise,” in Proc. IEEE ICASSP, 1979, pp. 208–211.
3. P. Boersma and D. Weenink, December 27, 2007, Praat: Doing Phonetics by Computer, ver. 5.0.02 [Online]. Available: http://www.fon. hum.uva.nl/praat
4. A. Bregman, Auditory Scene Analysis. Cambridge, MA: MIT Press, 1990.
5. G. J. Brown and M. Cooke “Computational auditory scene analysis,” Comput. Speech Lang., vol. 8, pp. 297–336, 1994.
6. D. S. Brungart, P. S. Chang, B. D. Simpson, and D. L. Wang “Isolating the energetic component of speech-on-speech masking with ideal time-frequency segregation,” J. Acoust. Soc. Amer., vol. 120, pp. 4007–4018, 2006.
7. C. de Boor, A Practical Guide to Splines. New York: Springer-Verlag, 1978.
8. H. Dillon, Hearing Aids. New York: Thieme Medical Publishers, 2001.
9. J. S. Garofolo, L. F. Lamel, W. M. Fisher, J. G. Fiscus, D. S. Pallett, and N. L. Dahlgren, 1993, DARPA TIMIT Acoustic Phonetic Continuous Speech Corpus. [Online]. Available: http://www.ldc.upenn.edu/Catalog/FDC93S1.html
10. G. Hu, “Monaural Speech Organization and Segregation,” Ph.D. dissertation, Biophys. Program, Ohio State Univ., Columbus, 2006.
11. G. Hu, 2006, 100 Nonspeech Sounds Online. [Online]. Available: http://www.cse.ohio-state.edu/pnl/corpus/HuCorpus.html
12. G. Hu and D. L. Wang, “Monaural speech segregation based on pitch tracking and amplitude modulation,” IEEE Trans. Neural Netw., vol. 15, no. 5, pp. 1135–1150, Sep. 2004.
13. G. Hu and D. L. Wang “Segregation of unvoiced speech from non-speech interference,” J. Acoust. Soc. Amer., vol. 124, pp. 1306–1319, 2008.
14. G. Hu and D. L. Wang “A tandem algorithm for pitch estimation and voiced speech segregation,” IEEE Trans. Audio, Speech, Lang. Process., vol. 18, no. 8, pp. 2067–2079, Nov. 2010.
15. K. Hu and D. L. Wang, “Incorporating spectral subtraction and noise type for unvoiced speech segregation,” in Proc. IEEE ICASSP, 2009, pp. 4425–4428.
16. Y. Hu and P. C. Loizou “A comparative intelligibility study of single-microphone noise reduction algorithms,” J. Acoust. Soc. Amer., vol. 122, no. 3, pp. 1777–1786, 2007.
17. IEEE “IEEE recommended practice for speech quality measurements,” IEEE Trans. Audio Electroacoust., vol. AE-17, pp. 225–246, 1969.
18. Z. Jin and D. L. Wang, “A supervised learning approach to monaural segregation of reverberant speech,” IEEE Trans. Audio, Speech, Lang. Process., vol. 17, no. 4, pp. 625–638, May 2009.
19. P. Ladefoged, Vowels and Consonants: An Introduction to the Sounds of Languages. Oxford, U.K.: Blackwell, 2001.
20. N. Li and P. C. Loizou “Factors influencing intelligibility of ideal binary-masked speech: Implications for noise reduction,” J. Acoust. Soc. Amer., vol. 123, pp. 1673–1682, 2008.
21. P. Li, Y. Guan, B. Xu, and W. Liu “Monaural speech separation based on computational auditory scene analysis and objective quality assessment of speech,” IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 6, pp. 2014–2023, Nov. 2006.
22. Y. Li and D. L. Wang “On the optimality of ideal binary time-frequency masks,” Speech Commun., vol. 51, pp. 230–239, 2009.
23. Z. Lin, R. A. Goubran, and R. M. Dansereau “Noise estimation using speech/non-speech frame decision and subband spectral tracking,” Speech Commun., vol. 49, pp. 542–557, 2007.
24. P. C. Loizou, Speech Enhancement: Theory and Practice. Boca Raton, FL: CRC, 2007.
25. R. Meddis “Simulation of auditory-neural transduction: Further studies,” J. Acoust. Soc. Amer., vol. 83, pp. 1056–1063, 1988.
26. H. Ney “On the probabilistic interpretation of neural network classifiers and discriminative training criteria,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 17, no. 2, pp. 107–119, Feb. 1995.
27. R. D. Patterson, I. Nimmo-Smith, J. Holdsworth, and P. Rice, “An efficient auditory filterbank based on the gammatone function,” Appl. Psychol. Unit, 1988, Cambridge, U.K., APU Rep. 2341.
28. M. H. Radfar and R. M. Dansereau “Single-channel speech separation using soft masking filtering,” IEEE Trans. Audio, Speech, Lang. Process., vol. 15, no. 8, pp. 2299–2310, Nov. 2007.
29. M. H. Radfar, R. M. Dansereau, and A. Sayadiyan, “A maximum likelihood estimation of vocal-tract-related filter characteristics for single channel speech separation,” EURASIP J. Audio, Speech, Music Process., vol. 2007, 2007, 10.1155/2007/84186, Article ID 84186, 15 pages.
30. Y. Shao, “Sequential Organization in Computational Auditory Scene Analysis,” Ph.D. dissertation, Dept. of Comput. Sci. and Eng., Ohio State Univ., Columbus, 2007.
31. S. Srinivasan, J. Samuelsson, and W. B. Kleijn “Codebook-based Bayesian speech enhancement for nonstationary environments,” IEEE Trans. Audio, Speech, Lang. Process., vol. 15, no. 2, pp. 441–452, Feb. 2007.
32. K. N. Stevens, Acoustic Phonetics. Cambridge, MA: MIT Press, 1998.
33. S. Vishnubhotla and C. Y. Espy-Wilson, “An algorithm for speech segregation of co-channel speech,” in Proc. IEEE ICASSP, 2009, pp. 109–112.
34. D. L. Wang, “On ideal binary mask as the computational goal of auditory scene analysis,” in Speech Separation by Humans and Machines, P. Divenyi, Ed. Norwell, MA: Kluwer, 2005, pp. 181–197.
35. D. L. Wang and G. J. Brown, “Separation of speech from interfering sounds based on oscillatory correlation,” IEEE Trans. Neural Netw., vol. 10, no. 3, pp. 684–697, May 1999.
36. Computational Auditory Scene Analysis: Principles, Algorithms and Applications, D. L. Wang and G. J. Brown, Eds. Hoboken, NJ: Wiley-IEEE Press, 2006.
37. D. L. Wang, U. Kjems, M. S. Pedersen, J. B. Boldt, and T. Lunner “Speech intelligibility in background noise with ideal binary time-frequency masking,” J. Acoust. Soc. Amer., vol. 125, pp. 2336–2347, 2009.