Abstract
Certain specific characteristics of speech are known to be particularly useful in diagnosing speech disorders by acoustic (perceptual) and instrumental methods. The most widely cited of these are described in this chapter, along with some comments as to their suitability for use in automated systems. Some of these features can be characterised by relatively simple signal processing operations, while others would ideally require a realistic model of the higher levels of neurological processing, including cognition. It is observed that even experts who come to the same ultimate decision regarding diagnosis, often differ in their assessment of individual speech characteristics. The difficulties of quantifying prosody and accurately identifying pitch epochs are highlighted, because of their importance in human perception of speech disorders.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Duffy JR (2000) Motor speech disorders: clues to neurologic diagnosis. In: Adler CH, Ahlskog JE (eds) Parkinson’s disease and movement disorders: diagnosis and treatment guidelines for the practicing physician. Humana Press, Totowa, pp 35–53
Fuchs PA (2005) Time and intensity coding at the hair cell’s ribbon synapse. J Physiol 566(1):7–12
HenrÃquez P, Alonso JB, Ferrer MA, Travieso CM, Godino-Llorente JI, DÃaz-de-MarÃa F (2009) Characterization of healthy and pathological voice through measures based on nonlinear dynamics. IEEE Trans Audio Speech Lang Process 17(6):1186–1195
Kent RD (1996) Hearing and believing: some limits to the auditory-perceptual assessment of speech and voice disorders. Am J Speech-Lang Pathol 5(3):7–23
Masaki A (2010) Optimizing acoustic and perceptual assessment of voice quality in children with vocal nodules. PhD thesis, Harvard-MIT Health Sciences and Technology
McHenry M (2011) An exploration of listener variability in intelligibility judgments. Am J Speech-Lang Pathol 20:119–123. doi:10.1044/1058-0360(2010/10-0059
Pentland A (2007) Social signal processing. IEEE Signal Process Mag 24(4):108–111
Ringeval F, Demouy J, Szaszák G, Chetouani M, Robel L, Xavier J, Cohen D, Plaza M (2010) Automatic intonation recognition for the prosodic assessment of language-impaired children. IEEE Trans Audio Speech Lang Process 19(5):1328–1342. doi:10.1109/TASL.2010.2090147
Schuller B, Batliner A, Seppi D, Steidl S, Vogt T, Wagner J, Devillers L, Vidrascu L, Amir N, Kessous L, Aharonson V (2007) The relevance of feature type for the automatic classification of emotional user states: low level descriptors and functionals. In: Proceedings of INTERSPEECH-2007, pp 2253–2256
Shera CA, Olson ES (eds) (2011) What fire is in mine ears: progress in auditory biomechanics. In: Proceedings of 11th international mechanics of hearing workshop. American Institute of Physics, Melville
van Santen JPH, Prud’hommeaux ET, Black LM (2009) Automated assessment of prosody production. Speech Commun 51(11):1082–1097. doi:10.1016/j.specom.2009.04.007
Ziegler W, Zierdt A (2008) Telediagnostic assessment of intelligibility in dysarthria: a pilot investigation of MVP-online. J Commun Disord 41(6):553–577
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 The Author(s)
About this chapter
Cite this chapter
Baghai-Ravary, L., Beet, S.W. (2013). Speech Production and Perception. In: Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders. SpringerBriefs in Electrical and Computer Engineering(). Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4574-6_2
Download citation
DOI: https://doi.org/10.1007/978-1-4614-4574-6_2
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-4573-9
Online ISBN: 978-1-4614-4574-6
eBook Packages: EngineeringEngineering (R0)