Comparing models of the combined-stimulation advantage for speech recognition

Christophe Micheyl, Andrew J. Oxenham

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)3970-3980
Number of pages11
JournalJournal of the Acoustical Society of America
Volume131
Issue number5
DOIs
StatePublished - May 2012

Bibliographical note

Funding Information:
This work was supported by NIH R01 DC05216. The authors are grateful to Dr. R. P. Carlyon, Dr. L. Demany, Dr. Y. Y. Kong, and to one anonymous reviewer, for helpful suggestions on an earlier version of the manuscript.

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