Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Qatar University Ins...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 2 versions
addClaim

Models of Speech Processing

Authors: Grosvald, Michael; Burton, Martha W.; Small, Steven L.;

Models of Speech Processing

Abstract

One of the fundamental questions about language is how listeners map the acoustic signal onto syllables, words, and sentences, resulting in understanding of speech. For normal listeners, this mapping is so effortless that one rarely stops to consider just how it takes place. However, studies of speech have shown that this acoustic signal contains a great deal of underlying complexity. A number of competing models seek to explain how these intricate processes work. Such models have often narrowed the problem to mapping the speech signal onto isolated words, setting aside the complexity of segmenting continuous speech. Continuous speech has presented a significant challenge for many models because of the high variability of the signal and the difficulties involved in resolving the signal into individual words. The importance of understanding speech becomes particularly apparent when neurological disease affects this seemingly basic ability. Lesion studies have explored impairments of speech sound processing to determine whether deficits occur in perceptual analysis of acoustic-phonetic information or in stored abstract phonological representations (e.g., Basso, Casati,& Vignolo, 1977; Blumstein, Cooper, Zurif,& Caramazza, 1977). Furthermore, researchers have attempted to determine in what ways underlying phonological/phonetic impairments may contribute to auditory comprehension deficits (Blumstein, Baker, & Goodglass, 1977). In this chapter, we discuss several psycholinguistic models of word recognition (the process of mapping the speech signal onto the lexicon), and outline how components of such models might correspond to the functional anatomy of the brain. We will also relate evidence from brain lesion and brain activation studies to components of such models. We then present some approaches that deal with speech perception more generally, and touch on a few current topics of debate. National Institutes of Health under grant NIH DC R01–3378 to the senior author (SLS)

Country
Qatar
Related Organizations
Keywords

Speech Processing, word recognition, normal speech processing

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green