Abstract
Speech and voice technologies are experiencing a profound review as new paradigms are sought to overcome some specific problems which can not be completely solved by classical approaches. Neuromorphic Speech Processing is an emerging area in which research is turning the face to understand the natural neural processing of speech by the Human Auditory System in order to capture the basic mechanisms solving difficult tasks in an efficient way. In the present paper a further step ahead is presented in the approach to mimic basic neural speech processing by simple neuromorphic units standing on previous work to show how formant dynamics -and henceforth consonantal features-, can be detected by using a general neuromorphic unit which can mimic the functionality of certain neurons found in the Upper Auditory Pathways. Using these simple building blocks a General Speech Processing Architecture can be synthesized as a layered structure. Results from different simulation stages are provided as well as a discussion on implementation details. Conclusions and future work are oriented to describe the functionality to be covered in the next research steps.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Delattre, P., Liberman, A., Cooper, F.: Acoustic loci and transitional cues for consonants. J. Acoust. Soc. Am. 27, 769–773 (1955)
Deller, J.R., Proakis, J.G., Hansen, J.H.: Discrete-Time Processing of Speech Signals. Macmillan, New York (1993)
Gómez, P., Godino, J.I., Alvarez, A., Martínez, R., Nieto, V., Rodellar, V.: Evidence of Glottal Source Spectral Features found in Vocal Fold Dynamics. In: Proc. of the ICASSP 2005, pp. 441–444 (2005)
Hermansky, H.: Should Recognizers Have Ears? In: ESCA-NATO Tutorial and Research Workshop on Robust Speech Recognition for Unknown Communication Channels, Pont-à-Mousson, France, April 17-18, 1997, pp. 1–10 (1997)
Ferrández, J.M.: Study and Realization of a Bio-inspired Hierarchical Architecture for Speech Recognition, Ph.D. Thesis, Universidad Politécnica de Madrid (1998) (in Spanish)
Gómez, P., Martínez, R., Rodellar, V., Ferrández, J.M.: Bio-inspired Systems in Speech Perception: An overview and a study case. In: IEEE/NML Life Sciences Systems and Applications Workshop (by invitation), National Institute of Health, Bethesda, Maryland, July 13-14 (2006)
Haykin, S.: Neural Networks - A comprehensive Foundation. Prentice-Hall, Upper Saddle River (1999)
Irino, T., Patterson, R.D.: A time-domain, level-dependent auditory filter: the gammachirp. J. Acoust. Soc. Am. 101(1), 412–419 (1997)
Jahne, B.: Digital Image Processing. Springer, Berlin (2005)
Mendelson, J.R., Cynader, M.S.: Sensitivity of Cat Primary Auditory Cortex (AI) Neurons to the Direction and Rate of Frequency Modulation. Brain Research 327, 331–335 (1985)
Mountcastle, V.B.: The columnar organization of the neocortex. Brain 120, 701–722 (1997)
Ojemann, G.A.: Organization of language cortex derived from investigation during neurosurgery. Sem. Neuros. 2, 297–305 (1990)
O’Shaughnessy, D.: Speech Communication. IEEE Press, Park Avenue (2000)
Rauschecker, J.P., Tian, B., Hauser, M.: Processing of Complex Sounds in the Macaque Nonprimary Auditory Cortex. Science 268, 111–114 (1995)
Sams, M., Salmening, R.: Evidence of sharp frequency tuning in human auditory cortex. Hearing Research 75, 67–74 (1994)
Schreiner, C.E.: Time Domain Analysis of Auditory-Nerve Fibers Firing Rates. Curr. Op. Neurobiol. 5, 489–496 (1995)
Secker, H., Searle, C.: Study and Realization of a Bio-inspired Hierarchical Architecture for Speech Recognition. J. Acoust. Soc. Am. 88(3), 1427–1436 (1990)
Sejnowski, T.J., Rosenberg, C.R.: Parallel networks that learn to pronounce English text. Complex Systems 1, 145–168 (1987)
Suga, N.: Cortical Computational Maps for Auditory Imaging. Neural Networks 3, 3–21 (1990)
Suga, N.: Basic Acoustic Patterns and Neural Mechanism Shared By Humans and Animals for Auditory Perception: A Neuroethologists view. In: Proceedings of Workshop on the Auditory bases of Speech Perception, ESCA, July 1996, pp. 31–38 (1996)
Waibel, A.: Neural Network Approaches for Speech Recognition. In: Furui, S., Sondhi, M.M. (eds.) Advances in Speech Signal Processing, pp. 555–597. Dekker, New York (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gómez-Vilda, P. et al. (2009). Detection of Speech Dynamics by Neuromorphic Units. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira’s Scientific Legacy. IWINAC 2009. Lecture Notes in Computer Science, vol 5601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02264-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-02264-7_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02263-0
Online ISBN: 978-3-642-02264-7
eBook Packages: Computer ScienceComputer Science (R0)