Perceptual features for automatic speech recognition in noisy environments

Speech Communication

Volumn 51, Issue 1, 2009, Pages 58-75

  Haque, Serajul ^a   Togneri, Roberto ^a   Zaknich, Anthony ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

Auditory system; Automatic speech recognition; Hidden Markov model; Perceptual features; Synaptic adaptation; Two tone suppression

Indexed keywords

BANDPASS FILTERS; CROSSINGS (PIPE AND CABLE); DEGRADATION; GAUSSIAN NOISE (ELECTRONIC); HIDDEN MARKOV MODELS; HIGH PASS FILTERS; IIR FILTERS; IMPULSE RESPONSE; MARKOV PROCESSES; POLARIZATION; SENSOR NETWORKS; SPEECH; SPEECH ANALYSIS; TRELLIS CODES; WAVE FILTERS; WHITE NOISE;

AUDITORY SYSTEM; AUTOMATIC SPEECH RECOGNITION; PERCEPTUAL FEATURES; SYNAPTIC ADAPTATION; TWO-TONE SUPPRESSION;

SPEECH RECOGNITION;

EID: 55049112969     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.specom.2008.06.002     Document Type: Article

References (38)

1. Abdelatty, A.M., Spiegel, J.V., Mueller, P., Haentjens, G., Berman, J., 1999. An acoustic-phonetic feature-based system for automatic phoneme recognition in continuous speech. In: Proc. IEEE Intertnat. Conf. on Acoust. Speech, and Signal Processing (ICASSP 1999).
2. Bloomberg, M., Carlson, R., Elenius, K., Granstrom, B., 1984. Auditory models and isolated word recognition. Q Prog. Statist. Rep., Speech Transmiss. Lab., Royal Institute of Technology, Stockholm, pp. 1-15.
3. Cohen J.R. Application of an auditory model to speech recognition. J. Acoust. Soc. Amer. 85 6 (1989) 2623-2629
4. Dolby R. An audio noise reduction system. J. Audio Eng. Soc. 15 4 (1967)
5. Frey D., Tsividis Y., Efthivoulidis G., and Krishnapura N. Syllabic-companding log domain filters. IEEE Trans. Circ. Systems II 48 4 (2001) 329-339
6. Gajić, B., Paliwal, K.K., 2003. Robust speech recognition using features based on zero-crossings with peak amplitudes. In: Proc. IEEE Internat. Conf. on Acoust. Speech, and Signal Processing (ICASSP 2003).
7. Gillick, L., Cox, S.J., 1989. Some statistical issues in the comparison of speech recognition algorithms. In: Proc. IEEE Internat. Conf. on Acoust. Speech, and Signal Processing (ICASSP 1989).
8. Ghitza O. Auditory models and human performance in tasks related to speech coding and speech recognition. IEEE Trans. Speech Audio Process. 2 1 (1988) 115-132
9. Ghulam, M., Fukuda, T., Horikawa, J., Nitta, T., 2005. Pitch-synchronous ZCPA (PS-ZCPA)-based feature extraction with auditory masking. In: Proc. IEEE Internat. Conf. on Acoust. Speech, and Signal Processing (ICASSP 2005).
10. Grayden, D.B., Burkitt, A.N., Kenny, O.P., Clarey, J.N., Paolini, A.G., Clark, G.M., 2004. A cochlear implant speech processing strategy based on an auditory model. In: Internat. Conf. on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2004), Melbourne, pp. 491-496.
11. Haque, S., Togneri, R., Zaknich, A., 2007. A temporal auditory model with adaptation for automatic speech recognition. In: Proc. IEEE Internat. Conf. on Acoust. Speech, and Signal Processing (ICASSP 2007).
12. Hayes M.H. Statistical Digital Signal Processing and Modeling (1996), John Wiley and Sons, Inc., New Jersey 72-73
13. Hermansky H., and Morgan N. RASTA processing of speech. IEEE Trans. Speech Audio Process. 2 (1994) 587-589
14. Hermansky, H., 1994. Speech beyond 10 ms (temporal filtering in feature domain). In: Proc. Internat. Workshop on Human Interface Technology, Aizu, Japan.
15. Holmberg M., Gelbart D., and Hemmert W. Automatic speech recognition with an adaptation model motivated by auditory processing. IEEE Trans. Audio, Speech, Lang. Process. 14 1 (2006) 44-49
16. Jankowski Jr. C.R., Vo H.H., and Lippman R.P. A comparison of signal processing front ends for automatic word recognition. IEEE Trans. Speech Audio Process. 3 (1995) 286-293
17. Kates J.M. Two-tone suppression in a cochlear model. IEEE Trans. Speech Audio Process. 3 5 (1995) 396-406
18. Kedem B. Spectral analysis and discrimination by zero-crossings. Proc. IEEE 74 11 (1986) 1477-1493
19. Kim D.S., Lee S.Y., and Kil R.M. Auditory processing of speech signals for robust speech recognition in real world noisy environments. IEEE Trans. Speech and Audio Process. 7 1 (1999) 55-69
20. Koopmans L.H. The Spectral Analysis of Time Series (1974), Academic Press, New York
21. Loughlin, P., Groutage, D., Rohrbaugh, R., 1997. Time-frequency analysis of acoustic transients. In: Proc. IEEE Internat. Conf. on Acoust. Speech, and Signal Processing (ICASSP 1997).
22. Lyon R.F., and Mead C. An analog electronic cochlea. IEEE Trans. Acoust. Speech Signal Process. 36 7 (1988) 1119-1134
23. Meddis R. Simulation of mechanical to neural transduction in the auditory receptor. J. Acoust. Soc. Amer. 79 3 (1988) 702-711
24. Moore B.C.J., and Glasberg B.R. Suggested formulae for calculating auditory-filter bandwidths and excitation patterns. J. Acoust. Soc. Amer. 74 3 (1983) 750-753
25. Oxenham A.J. Forward masking: adaptation or integration?. J. Acoust. Soc. Amer. 109 (2001) 732-741
26. Pitton J.W., Wang K., and Juang B. Time-frequency analysis and auditory modeling for automatic recognition of speech. Proc. IEEE 84 9 (1996) 1199-1215
27. Patterson R.D. Time-interval information in the auditory representation of speech sounds. J. Acoust. Soc. Amer. 105 2 (1999) 1305
28. Rhode W.S. Some observations on cochlear mechanics. J. Acoust. Soc. Amer. 64 1 (1978) 158-176
29. Ruggero M.A., Narayan S.S., Temchin A.N., and Recio A. Mechanical bases of frequency tuning and neural excitation at the base of the cochlea. Proc. Natl. Acad. Sci. USA 97 (2000) 11744-11750
30. Sachs M.B., Voigt H.F., and Young E.D. Auditory nerve representation of vowels in background noise. J. Neurophysiol. 50 1 (1983)
31. Seneff S. A joint synchrony/mean-rate model of auditory processing. J. Phonet. 85 1 (1988) 55-76
32. Smith R., and Zwislocki J.J. Short-term adaptation and incremental responses of single auditory-nerve fibres. Biol. Cyber. 17 (1975) 169-182
33. Spoor, A., Eggermont, J.J., Odenthal, D.W., 1976. Comparison of human and animal data concerning adaptation and masking of eighth nerve compound action potential. In: Ruber, J., Elberling, C., Solomon, G. (Eds.), Electrocochleography, Baltimore, University Park, MD, pp. 183-198.
34. Strope B., and Alwan A. A model of dynamic auditory perception and its application to robust word recognition. IEEE Trans. Speech Audio Process. 95 5 (1997) 451-464
35. Theodoridis S., and Koutroumbas K. Pattern Recognition (1999), Elsevier, San Diego, CA
36. Tchorz J., and Kollmeier B. A model of auditory perception as front-end for automatic speech recognition. J. Acoust. Soc. Amer. 106 4 (1999)
37. Turicchia L., and Sarpeshkar R. A bio-inspired companding strategy for spectral enhancement. IEEE Trans. Speech Audio Process. 13 2 (2005) 243-253
38. Westerman L., and Smith R.L. Rapid and short-term adaptation in auditory nerve responses. Hearing Res. 15 (1984) 249-260