Literature DB >> 22559370

Comparing models of the combined-stimulation advantage for speech recognition.

Christophe Micheyl1, Andrew J Oxenham.   

Abstract

The "combined-stimulation advantage" refers to an improvement in speech recognition when cochlear-implant or vocoded stimulation is supplemented by low-frequency acoustic information. Previous studies have been interpreted as evidence for "super-additive" or "synergistic" effects in the combination of low-frequency and electric or vocoded speech information by human listeners. However, this conclusion was based on predictions of performance obtained using a suboptimal high-threshold model of information combination. The present study shows that a different model, based on Gaussian signal detection theory, can predict surprisingly large combined-stimulation advantages, even when performance with either information source alone is close to chance, without involving any synergistic interaction. A reanalysis of published data using this model reveals that previous results, which have been interpreted as evidence for super-additive effects in perception of combined speech stimuli, are actually consistent with a more parsimonious explanation, according to which the combined-stimulation advantage reflects an optimal combination of two independent sources of information. The present results do not rule out the possible existence of synergistic effects in combined stimulation; however, they emphasize the possibility that the combined-stimulation advantages observed in some studies can be explained simply by non-interactive combination of two information sources.

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Year:  2012        PMID: 22559370      PMCID: PMC3356316          DOI: 10.1121/1.3699231

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  33 in total

1.  Using statistical decision theory to predict speech intelligibility. I. Model structure.

Authors:  H Müsch; S Buus
Journal:  J Acoust Soc Am       Date:  2001-06       Impact factor: 1.840

2.  Speech recognition in noise for cochlear implant listeners: benefits of residual acoustic hearing.

Authors:  Christopher W Turner; Bruce J Gantz; Corina Vidal; Amy Behrens; Belinda A Henry
Journal:  J Acoust Soc Am       Date:  2004-04       Impact factor: 1.840

3.  Integration across frequency bands for consonant identification.

Authors:  Diane Ronan; Ann K Dix; Phalguni Shah; Louis D Braida
Journal:  J Acoust Soc Am       Date:  2004-09       Impact factor: 1.840

4.  Acoustic simulations of combined electric and acoustic hearing (EAS).

Authors:  Michael F Dorman; Anthony J Spahr; Philipos C Loizou; Cindy J Dana; Jennifer S Schmidt
Journal:  Ear Hear       Date:  2005-08       Impact factor: 3.570

5.  The benefits of combining acoustic and electric stimulation for the recognition of speech, voice and melodies.

Authors:  Michael F Dorman; Rene H Gifford; Anthony J Spahr; Sharon A McKarns
Journal:  Audiol Neurootol       Date:  2007-11-29       Impact factor: 1.854

6.  Impact of low-frequency hearing.

Authors:  A Büchner; M Schüssler; R D Battmer; T Stöver; A Lesinski-Schiedat; T Lenarz
Journal:  Audiol Neurootol       Date:  2009-04-22       Impact factor: 1.854

7.  Binaural benefits for adults who use hearing aids and cochlear implants in opposite ears.

Authors:  Teresa Y C Ching; Paula Incerti; Mandy Hill
Journal:  Ear Hear       Date:  2004-02       Impact factor: 3.570

8.  Crossmodal integration in the identification of consonant segments.

Authors:  L D Braida
Journal:  Q J Exp Psychol A       Date:  1991-08

9.  Mathematical treatment of context effects in phoneme and word recognition.

Authors:  A Boothroyd; S Nittrouer
Journal:  J Acoust Soc Am       Date:  1988-07       Impact factor: 1.840

10.  Bimodal hearing benefit for speech recognition with competing voice in cochlear implant subject with normal hearing in contralateral ear.

Authors:  Helen E Cullington; Fan-Gang Zeng
Journal:  Ear Hear       Date:  2010-02       Impact factor: 3.570

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  6 in total

1.  Effects of contextual cues on speech recognition in simulated electric-acoustic stimulation.

Authors:  Ying-Yee Kong; Gail Donaldson; Ala Somarowthu
Journal:  J Acoust Soc Am       Date:  2015-05       Impact factor: 1.840

2.  Experiments on Auditory-Visual Perception of Sentences by Users of Unilateral, Bimodal, and Bilateral Cochlear Implants.

Authors:  Michael F Dorman; Julie Liss; Shuai Wang; Visar Berisha; Cimarron Ludwig; Sarah Cook Natale
Journal:  J Speech Lang Hear Res       Date:  2016-12-01       Impact factor: 2.297

3.  The contribution of visual information to the perception of speech in noise with and without informative temporal fine structure.

Authors:  Paula C Stacey; Pádraig T Kitterick; Saffron D Morris; Christian J Sumner
Journal:  Hear Res       Date:  2016-04-13       Impact factor: 3.208

4.  Predicting the Perceptual Consequences of Hidden Hearing Loss.

Authors:  Andrew J Oxenham
Journal:  Trends Hear       Date:  2016 Jan-Dec       Impact factor: 3.293

5.  Reduced acoustic and electric integration in concurrent-vowel recognition.

Authors:  Hsin-I Yang; Fan-Gang Zeng
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

6.  Effects of noise on integration of acoustic and electric hearing within and across ears.

Authors:  Shelby Willis; Brian C J Moore; John J Galvin; Qian-Jie Fu
Journal:  PLoS One       Date:  2020-10-15       Impact factor: 3.240

  6 in total

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