The purpose was to assess if phonemic categorization in sentential context is best explained by autonomous feedforward processing or by top-down feedback processing that affects phonemic representation. 11 listeners with normal hearing, ages 20–50 years, were asked to label consonants in /pi/ – /ti/ consonant-vowel (CV) stimuli in 9-step continua. One continuum was derived from natural tokens and the other was synthetically generated. The CV stimuli were presented in isolation and in three sentential contexts: a neutral context, a context favoring /p/, and a context favoring /t/. For both natural and synthetic stimuli, the isolated and neutral context sentences yielded significantly more /t/ responses than sentence contexts primed for either /p/ or /t/. No other conditions were significantly different. Results did not show easily explainable semantic context effects. Instead, data clustering was more readily explained by top-down feedback processing affecting phonemic representation.
Get full access to this article
View all access options for this article.
References
1.
American National Standards Institute. (2010) Specifications for audiometers (ANSI S3.6). New York: Author.
2.
BorskyS.TullerB.ShapiroL. P. (1998) “How to milk a coat”: The effects of semantic and acoustic information on phoneme categorization. Journal of the Acoustical Society of America, 103, 2670–2676.
3.
ConnineC. M. (1987) Constraints on interactive processes in auditory word recognition: The role of sentence context. Journal of Memory and Language, 26, 527–538.
4.
ConnineC. M.BlaskoD. G.HallM. (1991) Effects of subsequent sentence context in auditory word recognition: Temporal and linguistic constraints. Journal of Memory and Language, 30, 234–250.
5.
ConnineC. M.CliftonC. (1987) Interactive use of lexical information in speech perception. Journal of Experimental Psychology: Human Perception and Performance, 13, 291–299.
6.
CutlerA.MehlerJ.NorrisD.SeguiJ. (1987) Phoneme identification and the lexicon. Cognitive Psychology, 19, 141–177.
7.
DesrochesA. S.NewmanR. L.JoanisseM. F. (2009) Investigating the time course of spoken word recognition: Electrophysiological evidence for the influences of phonological similarity. Journal of Cognitive Neuroscience, 21, 1893–1906.
8.
EllmanJ. L.McClellandJ. L. (1988) Cognitive penetration of the mechanisms of perception: Compensation for coarticulation of lexically restored phonemes. Journal of Memory and Language, 27, 143–165.
9.
GanongW. F. (1980) Phonetic categorization in auditory word perception. Journal of Experimental Psychology, Human Perception and Performance, 6, 110–125.
10.
HedrickM.YoungerM. S. (2003) Labeling of /s/ and /S/ by listeners with normal and impaired hearing, revisited. Journal of Speech, Language, and Hearing Research, 46, 636–648.
11.
HedrickM.YoungerM. S. (2007) Perceptual weighting of stop consonant cues by normal and impaired listeners in reverberation versus noise. Journal of Speech, Language, and Hearing Research, 50, 254–269.
12.
KlattD. (1980) Software for a cascade/parallel formant synthesizer. Journal of the Acoustical Society of America, 67, 971–995.
13.
MagnusonJ. S.McMurrayB.TanenhausM. K.AslinR. N. (2003) Lexical effects on compensation for coarticulation: The ghost of Christmash past. Cognitive Science, 27, 285–298.
14.
MassaroD. W. (1989) Testing between the TRACE model and the fuzzy logical model of speech perception. Cognitive Psychology, 21, 398–421.
15.
McClellandJ. L.ElmanJ. L. (1986) The TRACE model of speech perception. Cognitive Psychology, 18, 1–86.
16.
McClellandJ. L.MirmanD.HoltL. (2006) Are there interactive processes in speech perception?Trends in Cognitive Sciences, 10, 363–369.
17.
MesgaraniN.ChangE. (2012) Selective cortical representation of attended speaker in multi-talker speech perception. Nature, 485, 233–237.
18.
MillerJ. L.GreenK.SchermerT. M. (1984) A distinction between the effects of sentential speaking rate and semantic congruity on word identification. Perception & Psychophysics, 36, 329–337.
19.
MirmanD.McClellandJ. L.HoltL. L. (2006) An interactive Hebbian account of lexically guided tuning of speech perception. Psychonomic Bulletin Review, 13, 958–965.
20.
MirmanD.McClellandJ. L.HoltL. L.MagnusonJ. S. (2008) Effects of attention on the strength of lexical influences on speech perception: Behavioral experiments and computational mechanisms. Cognitive Science, 32, 398–417.
21.
NorrisD. G. (1994) A connectionist model of continuous speech recognition. Cognition, 52, 189–234.
22.
NorrisD. G.McQueenJ. M.CutlerA. (2000) Merging information in speech recognition: Feedback is never necessary. Behavioral and Brain Sciences, 23, 299–370.
23.
PittM. A.McQueenJ. M. (1998) Is compensation for coarticulation mediated by the lexicon?Journal of Memory and Language, 39, 347–370.
24.
SamuelA. G. (1981) Phonemic restoration: Insights from a new methodology. Journal of Experimental Psychology, General, 110, 474–494.
25.
SamuelA. G. (1996) Does lexical information influence the perceptual restoration of phonemes?Journal of Experimental Psychology, General, 125, 28–51.
26.
SamuelA. G. (2001) Knowing a word affects the fundamental perception of the sounds within it. Psychological Science, 12, 348–351.
27.
van AlphenP.McQueenJ. M. (2001) The time-limited influence of sentential context on function word identification. Journal of Experimental Psychology: Human Perception and Performance, 27, 1057–1071.
