Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Reflexive and Reflective Auditory Feedback Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Binaural Technology for Machine Speech Recognition and Understanding

Authors : Richard M. Stern, Anjali Menon

Published in: The Technology of Binaural Understanding

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

It is well known that binaural processing is very useful for separating incoming sound sources as well as for improving speech intelligibility in reverberant environments. This chapter describes and compares a number of ways in which automatic-speech-recognition accuracy in difficult acoustical environments can be improved through the use of signal processing techniques that are motivated by our understanding of binaural perception and binaural technology. These approaches are all based on the exploitation of interaural differences in arrival time and intensity of the signals arriving at the two ears to separate signals according to direction of arrival and to enhance the desired target signal. Their structure is motivated by classic models of binaural hearing as well as the precedence effect. We describe the structure and operation of a number of methods that use two or more microphones to improve the accuracy of automatic-speech-recognition systems operating in cluttered, noisy, and reverberant environments. The individual implementations differ in the methods by which binaural principles are imposed on speech processing, and in the precise mechanism used to extract interaural time and intensity differences. Algorithms that exploit binaural information can provide substantially improved speech-recognition accuracy in noisy, cluttered, and reverberant environments compared to baseline delay-and-sum beamforming. The type of signal manipulation that is most effective for improving performance in reverberation is different from what is most effective for ameliorating the effects of degradation caused by spatially-separated interfering sound sources.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
previous chapter A Virtual Testbed for Binaural Agents
next chapter Modeling Binaural Speech Understanding in Complex Situations
Literature
Aarabi, P., and G. Shi. 2004. Phase-based dual-microphone robust speech enhancment. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34: 1763–1773.
Allen, J.B., D.A. Berkley, and J. Blauert. 1977. Multimicrophone signal-processing technique to remove room reverberation from speech signals. Journal of the Acoustical Society of America 62 (4): 912–915.ADS
Allen, J.B., and L.R. Rabiner. 1977. A unified approach to short-time Fourier analysis and synthesis. Proceedings of the IEEE 65 (11): 1558–1564.
Araki, S., T. Hayashi, M. Delcroix, M. Fujimoto, K. Takeda, and T. Nakatani. 2015. Exploring multi-channel features for denoissing-autoencoder-based speech enhancement. In Proceedings on IEEE International Conference on Acoustics, Speech and Signal Processing, 116–120
Beutelmann, R., and T. Brand. 2006. Prediction of speech intelligibility in spatial noise and reverberation for normal-hearing and hearing-impaired listeners. Journal of Acoustical Society of America 120: 331–342.ADS
Beutelmann, R., T. Brand, and B. Kollmeier. 2010. Revision, extension, and evaluation of a binaural speech intelligibility model. Journal of Acoustical Society of America 127: 2479–2497.ADS
Blauert, J. 1980. Modeling of interaural time and intensity difference discrimination. In Psychophysical, Physiological, and Behavioural Studies in Hearing, eds. G. van den Brink, and F. Bilsen, 412–424. Delft: Delft University Press.
Blauert, J. 1983. Review paper: Psychoacoustic binaural phenomena. In Hearing–Physiologica Bases and Psychophysics, eds. R. Klinke, and R. Hartmann, 182–189. Heidelberg: Springer-Verlag.
Blauert, J. 1997. Spatial Hearing: The Psychophysics of Human Sound Localization, 2nd ed. Cambridge, MA: MIT Press.
Blauert, J., and W. Cobben. 1978. Some considerations of binaural cross-correlation analysis. Acustica 39: 96–103.
Bodden, M. 1993. Modelling human sound-source localization and the cocktail party effect. Acta Acustica 1: 43–55.
Bodden, M., and Anderson, T.R. 1995. A binaural selectivity model for speech recognition. In Proceedings of Eurospeech 1995 (European Speech Communication Association).
Boll, S.F. 1979. Suppression of acoustic noise in speech using spectral subtraction. IEEE Transactions on Acoustics, Speech, and Signal Processing 27(2), 113–120.
Bourlard, H., and Morgan, N. 1994. Connectionist Speech Recognition: A hybrid approach. Kluwer Academic Publishers.
Braasch, J. 2005. Modelling of binaural hearing. In Communication Acoustics, ed. J. Blauert, Chap. 4, 75–108. Berlin: Springer-Verlag
Breebaart, J., S. van de Par, and A. Kohlrausch. 2001a. Binaural processing model based on contralateral inhibition. I. Model structure. Journal of the Acoustical Society of America 110: 1074–1088.ADS
Breebaart, J., S. van de Par, and A. Kohlrausch. 2001b. Binaural processing model based on contralateral inhibition. II. Dependence on spectral parameters. Journal of the Acoustical Society of America 110: 1089–1103.ADS
Breebaart, J., S. van de Par, and A. Kohlrausch. 2001c. Binaural processing model based on contralateral inhibition. III. Dependence on temporal parameters. Journal of the Acoustical Society of America 110: 1117–1125.
Bregman, A.S. 1990. Auditory Scene Analysis. Cambridge, MA: MIT Press.
Brown, G.J., and M.P. Cooke. 1994. Computational auditory scene analysis. Computer Speech and Language 8: 297–336.
Brown, G.J., S. Harding, and J.P. Barker, 2006. Speech separation based on the statistics of binaural auditory features. In Proceedings of IEEE International Conference Acoustical, Speech, and Signal Processing, vol. V, 949 – 952.
Brown, G.J., and K.J. Palomäki. 2011. A computational model of binaural speech recognition: Role of across-frequency vs. within-frequency processing and internal noise. Speech Communication 53: 924–940.
Burkhard, M.D., and R.M. Sachs. 1975. Anthroponetric manikin for acoustic research. Journal of the Acoustical Society of America 58: 214–222.ADS
Cantu, M. 2018. Sound source segregation of multiple concurrent talkers via short-time target cancellation. Ph.D. thesis, Boston University.
Cho, B.J., H. Kwon, J.-W. Cho, C. Kim, R.M. Stern, and H.-M. Park. 2016. A subband-based stationary-component suppression method using harmonics and power ratio for reverberant speech recognition. IEEE Signal Processing Letters 23 (6): 780–784.ADS
Colburn, H.S. 1969. Some physiological limitations on binaural performance. Ph.D. thesis, Massachusetts Institute of Technology.
Colburn, H.S. 1973. Theory of binaural interaction based on auditory-nerve data. I. general strategy and preliminary results on interaural discrimination. Journal of the Acoustical Society of America 54: 1458–1470.ADS
Colburn, H.S., and N.I. Durlach. 1978. Models of binaural interaction. In Hearing, ed. E.C. Carterette, and M. P. Friedmann, Vol. IV of Handbook of Perception, Chap. 11, 467–518. New York: Academic Press
Colburn, H.S., and A. Kulkarni. 2005. Models of sound localization. In Sound Source Localization, eds. R. Fay, and T. Popper, Springer Handbook of Auditory Research, Chap. 8, 272–316. Springer-Verlag
Cooke, M., P. Green, L. Josifovski, and A. Vizinho. 2001. Robust automatic speech recognition with missing and unreliable acoustic data. Speech Communication 34: 267–285.MATH
Cooke, M.P., and D. P.W. Ellis. 2001. The auditory organization of speech and other sources in listeners and computational models. Speech Communication 35, 141–177.
Davis, S.B., and P. Mermelstein. 1980. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Transactions on Acoustics, Speech, and Signal Processing 28: 357–366.
Dempster, A.P., N.M. Laird, and D.B. Rubin. 1977. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society Series B 39: 1–38.MathSciNetMATH
DeSimio, M.P., T.R. Anderson, and J.J. Westerkamp. 1996. Phoneme recognition with a model of binaural hearing. IEEE Transactions on Speech and Audio Processing 4: 157–166.
Dietz, M., J.H. Lestang, P. Majdak, R.M. Stern, T. Marquardt, S.D. Ewert, W.M. Hartmann, and D.F.M. Goodman. 2017. A framework for testing and comparing binaural models. Hearing Research 360: 92–106.
Dietz, M., T. Marquardt, N.H. Salminen, and D. McAlpine. 2013. Emphasis of spatial cues in the temporal fine structure during the rising segments of amplitude-modulated sounds. Proceedings of the National Academy of Sciences of the United States of America 110: 15151–15156.ADS
Domnitz, R.H., and H.S. Colburn. 1976. Analysis of binaural detection models for dependence on interaural target parameters. Journal of the Acoustical Society of America 59: 599–601.ADS
Domnitz, R.H., and H.S. Colburn. 1977. Lateral position and interaural discrimination. Journal of the Acoustical Society of America 61: 1586–1598.ADS
Droppo, J. 2013. Feature compensation. In Techniques for Noise Robustness in Automatic Speech Recognition, ed. T. Virtanen, B. Raj, and R. Singh, Chap. 9. Wiley
Durlach, N.I. 1963. Equalization and cancellation theory of binaural masking level differences. Journal of the Acoustical Society of America 35 (8): 1206–1218.ADS
Durlach, N.I. 1972. Binaural signal detection: Equalization and cancellation theory. In Foundations of Modern Auditory Theory, vol. 2, ed. J.V. Tobias, 369–462. New York: Academic Press.
Durlach, N.I., and H.S. Colburn. 1978. Binaural phenomena. In Hearing, ed. E.C. Carterette, and M.P. Friedman, 365–466., Vol. IV of Handbook of Perception New York: Academic Press.
Faller, C., and J. Merimaa. 2004. Sound localization in complex listening situations: Selection of binaural cues based on interaural coherence. Journal of the Acoustical Society of America 116 (5): 3075–3089.ADS
Fan, N., J. Du, and L.-R. Dai. 2016. A regression approach to binaural speech segregation via deep neural networks. In Proceedings of IEEE International Symposium on Chinese Spoken Language Processing, 116–120.
Flanagan, J.L., J.D. Johnston, R. Zahn, and G.W. Elko. 1985. Computer-steered microphone arrays for sound transduction in large rooms. Journal of the Acoustical Society of America 78: 1508–1518.ADS
Gaik, W. 1993. Combined evaluation of interaural time and intensity differences: Psychoacoustic results and computer modeling. Journal of the Acoustical Society of America 94: 98–110.ADS
Gilkey, R.H., and Anderson, T.A. (eds.). 1997. Binaural and Spatial Hearing in Real and Virtual Environments. Psychology Press.
Gold, B., N. Morgan, and D. Ellis. 2011. Speech and Audio Signal Processing, 2nd ed. Wiley Interscience.
Goodfellow, I., Y. Bengio, and A. Courville. 2016. Deep Learning. MIT Press.
Harding, S., J. Barker, and G.J. Brown. 2006. Mask estimation for missing data speech recognition based on statistics of binaural interaction. IEEE Transactions on Speech and Audio Processing 14: 58–67.
Hartung, K., and C. Trahiotis. 2001. Peripheral auditory processing and investigations of the “precedence effect” which utilize successive transient stimuli. Journal of the Acoustical Society of America 110 (3): 1505–1513.
Hawley, M.L., R.Y. Litovsky, and H.S. Colburn. 1999. Speech intelligibility and localization in a multi-source environment. Journal of the Acoustical Society of America 105: 3436–3448.ADS
Haykin, S. 2018. Neural Networks And Learning Machines, 3rd ed. Springer.
Hermansky, H. 1990. Perceptual linear predictive (PLP) analysis of speech. Journal of the Acoustical Society of America 87 (4): 1738–1752.
Hermansky, H., D.P.W. Ellis, and S. Sharma. 2000. Tandem connectionist feature extraction for conventional hmm systems. In Proceedings of the IEEE ICASSP, 1635–1638.
Hermansky, H., and N. Morgan. 1994. RASTA processing of speech. IEEE Transactions on Speech and Audio Processing 2: 578–589.
Hinton, G., L. Deng, D. Yu, G.E. Dahl, and Mohamed, A., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T. N., and Kingsbury, B. 2012. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Processing Magazine 29, 82–97.
Jeffress, L.A. 1948. A place theory of sound localization. Journal of Comparative Physiology, Psychology 41: 35–39.
Jeub, M., M. Dorbecker, and P. Vary. 2011a. Semi-analytical model for the binaural coherence of noise fields. IEEE Signal Processing Letters 18 (3): 197–200.ADS
Jeub, M., C. Nelke, C. Beaugeant, and P. Vary. 2011b. Blind estimation of the coherent-to-diffuse energy ratio from noisy speech signals. In Proceedings of the\(19^{th}\)European Signal Processing Conference.
Jeub, M., M. Schafer, T. Esch, and P. Vary. 2010. Model-based dereverberation preserving binaural cues. IEEE Transactions on Audio, Speech, and Language Processing 18 (7): 1732–1745.
Jeub, M., M. Schafer, and P. Vary. 2009. A binaural room impulse response database for the evaluation of dereverberation algorithms. In Proceedings on\(16^{th}\)International Conference on Digital Signal Processing, 1–5.
Jiang, Y., D. Wang, R. Liu, and Z. Feng. 2014. Binaural classification for reverberant speech segregation using deep neural networks. IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (12): 2112–2121.
Johnson, D.H., and D.E. Dudgeon. 1993. Array Signal Processing: Concepts and Techniques. Englewood Cliffs NJ: Prentice-Hall.MATH
Kates, J.M. 1991. A time-domain digital cochlear model. IEEE Transaction on Signal Processing 39: 2573–2592.ADS
Kim, C., C. Khawand, and R.M. Stern. 2012. Two-microphone source separation algorithm based on statistical modeling of angle distributions. In Proceedings of the IEEE International Conference Acoustical, Speech and Signal Processing.
Kim, C., K. Kumar, B. Raj, and R.M. Stern. 2009. Signal separation for robust speech recognition based on phase difference information obtained in the frequency domain. In Proceedings of the Interspeech Conference.
Kim, C., K. Kumar, and R.M. Stern. 2011. Binaural sound source separation motivated by auditory processing. In Proceedings of the Interspeech Conference, Prague, Czech Republic, vol. 23, 780–784.
Kim, C., and R.M. Stern. 2010. Nonlinear enhancement of onset for robust speech recognition. In Proceedings of the Interspeech Conference. Makuhari, Japan
Kim, C., and R.M. Stern. 2016. Power-normalized cepstral coefficients (PNCC) for robust speech recognition. IEEE Transactions on Audio, Speech, and Language Processing 24(7), 1315–1329.
Kim, C., R.M. Stern, K. Eom, and J. Kee. 2010. Automatic selection of thresholds for signal separation algorithms based on interaural delay. In Proceedings of the Interspeech Conference. Makuhari, Japan.
Kohonen, T. 1989. The neural phonetic typewriter. IEEE Computer Magazine, 11–22.
Kohlrausch, A., J. Braasch, D. Kolossa, and J. Blauert. 2013. An introduction to binaural processing. In The Technology of Binarual Listening, ed. J. Blauert., Springer and ASA Press.
Kumatani, K., J. McDonough, and B. Raj. 2012. Microphone array processing for robust speech recognition. IEEE Signal Processing Magazine 29 (6): 127–140.ADS
Lindemann, W. 1986a. Extension of a binaural cross-correlation model by contralateral inhibition. I. simulation of lateralization for stationary signals. Journal of the Acoustical Society of America 80: 1608–1622.ADS
Lindemann, W. 1986b. Extension of a binaural cross-correlation model by contralateral inhibition. II. the law of the first wavefront. Journal of the Acoustical Society of America 80: 1623–1630.ADS
Lippmann, R.P. 1987. An introduction to computing with neural nets. IEEE ASSP Magazine 4 (2): 4–22.
Lippmann, R.P. 1989. Review of neural networks for speech recognition. Neural Computation 1 (1): 1–38.
Litovsky, R.Y., S.H. Colburn, W.A. Yost, and S.J. Guzman. 1999. The precedence effect. Journal of the Acoustical Society of America 106: 1633–1654.ADS
Lyon, R.F. 1984. Computational models of neural auditory processing. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing of the International Conference on Acoustics, Speech and Signal Processing, 36.1.1–36.1.4.
Mandel, M.I., R.J. Weiss, and D.P.W. Ellis. 2010. Model-based expectation-maximization source separation and localization. IEEE Transactions on Audio, Speech, and Language Processing 18 (2): 382–394.
Martin, K.D. 1997. Echo suppression in a computational model of the precedence effect. In Proceedings of the IEEE Mohonk Workshop on Applications of Signal Processing to Acoustics and Audio.
May, T., S.V.D. Par, and A. Kohlrausch. 2012. A binaural scene analyzer for joint localization and recognition of speakers in the presence of interfering noise sources and reverberation. IEEE Transactions on Audio, Speech, and Language Processing 20: 108–121.
May, T., S. van de Par, and A. Kohlrausch. 2011. A probabilistic model for robust localization based on a binaural auditory front-end. IEEE Transactions on Audio, Speech, and Language Processing 19 (1): 1–13.
Mehrgardt, S., and V. Mellert. 1977. Transformation charactersitics of the external human ear. Journal of the Acoustical Society of America 61: 1567–1576.ADS
Menon, A. 2018. Robust recognition of binaural speech signals using techniques based on human auditory processing. Ph.D. thesis, Carnegie Mellon University.
Mi, J., and H.S. Colburn. 2016. A binaural grouping model for predicting speech intelligibility in multitalker environments. Trends in Hearing 20: 1–12.
Mi, J., M. Groll, and H.S. Colburn. 2017. Comparison of a target-equalization-cancellation approach and a localization approach to source separation. Journal of the Acoustical Society of America 142 (5): 2933–2941.ADS
Miao, Y., and F. Metze. 2017. End-to-end architectures for speech recognition. In New Era for Robust Speech Recognition: Exploiting Deep Learning, ed. Watanabe, S., M. Delcroix, F. Metze, and J.R. Hershey, 299–323. Springer International Publishing
Mitra, V., H. Franco, R. Stern, J.V. Hout, L. Ferrer, M. Graciarena, W. Wang, D. Vergyri, A. Alwan, and J.H.L. Nansen. 2017. Robust features in deep learning-based speech recognition. In New Era for Robust Speech Recognition: Exploiting Deep Learning, ed. Watanabe, S., M. Delcroix, F. Metze, and J.R. Hershey, 183–212. Springer International Publishing
Moore, B.C.J. 2012. An Introduction to the Psychology of Hearing, 6th ed. Bingley UK, London: Emerald Group Publishing Ltd.
Moreno, P.J., B. Raj, and R.M. Stern. 1996. A vector Taylor series approach for environment-independent speech recognition. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 733–736
Osman, E. 1971. A correlation model of binaural masking level differences. Journal of the Acoustical Society of America 50: 1494–1511.ADS
Palomäki, K.J., G.J. Brown, and D.L. Wang. 2004. A binaural processor for missing data speech recognition in the presence of noise and small-room reverberation. Speech Communication 43 (4): 361–378.
Park, H.-M., and R.M. Stern. 2009. Spatial separation of speech signals using continuously-variable weighting factors estimated from comparisons of zero crossings. Speech Communication Journal 51 (1): 15–25.
Patterson, R.D., I. Nimmo-Smith, J. Holdsworth, and P. Rice. 1988. An efficient auditory filterbank based on the gammatone function, Applied Psychology Unit (APU) Report 2341. Cambridge UK
Rabiner, L.R. 1989. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77 (2): 257–286.
Rabiner, L.R., and B.-H. Juang. 1993. Fundamentals of Speech Recognition. Prentice-Hall.
Raj, B., M.L. Seltzer, and R.M. Stern. 2004. Reconstruction of missing features for robust speech recognition. Speech Communication 43 (4): 275–296.
Raj, B., and R.M. Stern. 2005. Missing-feature approaches in speech recognition. IEEE Signal Processing Magazine 22 (5): 101–115.ADS
Rickard, S. 2007. The DUET blind source separation algorithm. In Blind Speech Separation, ed. Makino, S., T. Lee, and H.E. Sawada. New York: Springer-Verlag.
Roman, N., S. Srinivasan, and D. Wang. 2006. Binaural segregation in multisource. Journal of the Acoustical Society of America 120: 4040–4051.
Roman, N., D.L. Wang, and G.J. Brown. 2003. Speech segregation based on sound localization. Journal of the Acoustical Society of America 114 (4): 2236–2252.ADS
Rosenblatt, R. 1959. Principles of Neurodynamics. New York: Spartan Books.
Schroeder, M.R. 1977. New viewpoints in binaural interactions. In Psychophysics and Physiology of Hearing, ed. Evans, E.F. and J.P. Wilson, 455–467. London: Academic Press
Shamma, S.A., N. Shen, and P. Gopalaswamy. 1989. Binaural processing without neural delays. Journal of the Acoustical Society of America 86: 987–1006.ADS
Shao, Y., and D.L. Wang. 2008. Robust speaker identification using auditory features and computational auditory scene analysis. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 1589–1592
Srinivasan, S., M. Roman, and D. Wang. 2006. Binary and ratio time-frequency masks for robust speech recognition. Speech Communication 48: 1486–1501.
Stecker, G.C., J.D. Ostreicher, and A.D. Brown. 2013. Temporal weighting functions for interaural time and level differences. III. Temporal weighting for lateral position judgments. Journal of the Acoustical Society of America 134: 1242–1252.
Stern, R.M., and H.S. Colburn. 1978. Theory of binaural interaction based on auditory-nerve data. IV. A model for subjective lateral position. Journal of the Acoustical Society of America 64: 127–140.
Stern, R.M., and Trahiotis, C. 1995. Models of binaural interaction. In Hearing, ed. Moore, B.C.J., Handbook of Perception and Cognition, 2 ed, Chap. 10, 347–386. New York: Academic.
Stern, R.M., and C. Trahiotis. 1996. Models of binaural perception. In Binaural and Spatial Hearing in Real and Virtual Environments, ed. Gilkey, R. and T.R. Anderson, Chap. 24, 499–531. Lawrence Erlbaum Associates
Stern, R.M., D. Wang, and G.J. Brown. 2006. Binaural sound localization. In Computational Auditory Scene Analysis, ed. Wang, D., and G.J: Brown, Chap. 5. Wiley-IEEE Press
Stern, R.M., A.S. Zeiberg, and C. Trahiotis. 1988. Lateralization of complex binaural stimuli: a weighted image model. Journal of the Acoustical Society of America 84: 156–165.ADS
Stevens, S.S., J. Volkman, and E. Newman. 1937. A scale for the measurement of the psychological magnitude pitch. Journal of the Acoustical Society of America 8 (3): 185–190.ADS
Stockham, T.G., T.M. Cannon, and R.B. Ingrebretsen. 1975. Blind deconvolution through digital signal processing. Proceedings of the IEEE 63 (4): 678–692.
Thiergart, O., G. Del Galdo, and E.A. Habets. 2012. Signal-to-reverberant ratio estimation based on the complex spatial coherence between omnidirectional microphones. In: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 309–312.
Trahiotis, C., L.R. Bernstein, R.M. Stern, and T.N. Buell. 2005. Interaural correlation as the basis of a working model of binaural processing: An introduction. In Sound Source Localization, ed. R. Fay, and T. Popper, 238–271., Springer Handbook of Auditory Research. Heidelberg: Springer-Verlag.
Van Trees, H.L. 2004. Detection, Estimation, and Modulation Theory: Optimum Array Processing. Wiley.
Virtanen, T., B. Raj, and R. Singh, eds. 2012. Noise-Robust Techniques for Automatic Speech Recognition. Wiley.
Wallach, H.W., E.B. Newman, and M.R. Rosenzweig. 1949. The precedence effect in sound localization. American Journal of Psychology 62: 315–337.
Wan, R., N.I. Durlach, and H.S. Colburn. 2010. Application of an extended equalization-cancellation model to speech intelligibility with spatially distributed maskers. Journal of the Acoustical Society of America 128: 3678–3690.ADS
Wan, R., N.I. Durlach, and H.S. Colburn. 2014. Application of a short-time version of the equalization-cancellation model to speech intelligibility experiments with speech maskers. Journal of the Acoustical Society of America 136: 768–776.ADS
Wang, D., and G.J. Brown, eds. 2006. Computational Auditory Scene Analysis: Principles, Algorithms, and Applications. Wiley-IEEE Press.
Wang, D.L., and J. Chen. 2018. Supervised speech separation based on deep learning: An overview. IEEE Transactions on Audio, Speech, and Language Processing 26: 1702–1726.ADS
Wang, Y., and D.L. Wang. 2013. Towards scaling up classification-based speech separation. IEEE Transactions on Audio, Speech, and Language Processing 21: 1381–1390.
Watanabe, S., M. Delcroix, F. Metze, and J.R. Hershey, eds. 2017. New Era for Robust Speech Recognition: Exploiting Deep Learning. Springer International.
Westermann, A., J.M. Buchholz, and T. Dau. 2013. Binaural dereverberation based on interaural coherence histograms. The Journal of the Acoustical Society of America 133 (5): 2767–2777.
Wightman, F.L., and D.J. Kistler. 1989a. Headphone simulation of free-field listening. I: Stimulus synthesis. The Journal of the Acoustical Society of America 85: 858–867.ADS
Wightman, F.L., and D.J. Kistler. 1989b. Headphone simulation of free-field listening. II: Psychophysical validation. Journal of the Acoustical Society of America 87: 868–878.ADS
Wightman, F.L., and D.J. Kistler. 1999. Resolution of front-back ambiguity in spatial hearing by listener and source movement. The Journal of the Acoustical Society of America 105 (5): 2841–2853.ADS
Woodruff, J., and D.L. Wang. 2013. Binaural detection, localization, and segregation in reverberant environments based on joint pitch and azimuth cues. IEEE Transactions on Audio, Speech, and Language Processing 21: 806–815.
Yost, W.A. 1981. Lateral position of sinusoids presented with intensitive and temporal differences. Journal of the Acoustical Society of America 70: 397–409.ADS
Yost, W.A. 2013. Fundamentals of Hearing: An Introduction, 5th ed. Burlington MA: Academic Press.
Yu, Y., W. Wang, and P. Han. 2016. Localization based stereo speech source separation using probabilistic time-frequency masking and deep neural networks. EURASIP Journal on Audio, Speech, and Music Processing 2016: 1–18.
Zhang, X., M.G. Heinz, I.C. Bruce, and L.H. Carney. 2001. A phenomenological model for the response of auditory-nerve fibers: I. nonlinear tuning with compression and suppression. Journal of the Acoustical Society of America 109: 648–670.
Zhang, X., and D. Wang. 2017. Deep learning based binaural speech separation in reverberant environments. IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (5): 1075–1084.
Zheng, C., A. Schwarz, W. Kellermann, and X. Li. 2015. Binaural coherent-to-diffuse-ratio estimation for dereverberation using an ITD model. In Proceedings of the\(23^{rd}\)European Signal Processing Conference (EUSIPCO), 1048–1052.
Zilany, M.S.A., I.C. Bruce, P.C. Nelson, and L.H. Carney. 2009. A phenomenological model of the synapse between the inner hair cell and auditory nerve: Long-term adaptation with power-law dynamics. Journal of the Acoustical Society of America 125: 2390–2412.ADS
Zurek, P.M. 1993. Binaural advantages and directional effects in speech intelligibility. In Acoustical Factors Affecting Hearing Aid Performance, ed. G.A. Studebaker, and I. Hochberg. Boston: Allyn and Bacon.
Zurek, P.M., R.L. Freyman, and U. Balakrishnan. 2004. Auditory target detection in reverberation. Journal of the Acoustical Society of America 115 (4): 1609–1620.ADS
Metadata
Title
Binaural Technology for Machine Speech Recognition and Understanding
Authors
Richard M. Stern
Anjali Menon
Copyright Year
2020
Book
The Technology of Binaural Understanding

Print ISBN: 978-3-030-00385-2

Electronic ISBN: 978-3-030-00386-9

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-00386-9_18

Premium Partner

    Image Credits