Presentation level determination for CV tokens using a computer-controlled adaptive procedure

Wall, Lida G.; Davidson, Stephanie A.; Fox, Robert

doi:10.1016/0021-9924(89)90016-6

Cited by 1 publication

(1 citation statement)

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“…While it is less common to use monosyllabic words, or closed-set phoneme materials, within adaptive SRT procedures, previous studies have demonstrated the efficacy of such methods (Tecca and Binnie, 1982;Mackie and Dermody, 1986;Wall et al, 1989;Liu and Eddins, 2012). Three separate measures of SRT were obtained for each processing strategy and each target stimulus set (consonant and vowel) by using three adaptive rules (described below) that converged to 70.7%, 50%, and 29.3% correct speech reception.…”

Section: E Speech Reception Testingmentioning

confidence: 99%

Two-microphone spatial filtering provides speech reception benefits for cochlear implant users in difficult acoustic environments

Goldsworthy

Delhorne

Desloge

et al. 2014

The Journal of the Acoustical Society of America

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This article introduces and provides an assessment of a spatial-filtering algorithm based on two closely-spaced ($1 cm) microphones in a behind-the-ear shell. The evaluated spatial-filtering algorithm used fast ($10 ms) temporal-spectral analysis to determine the location of incoming sounds and to enhance sounds arriving from straight ahead of the listener. Speech reception thresholds (SRTs) were measured for eight cochlear implant (CI) users using consonant and vowel materials under three processing conditions: An omni-directional response, a dipole-directional response, and the spatial-filtering algorithm. The background noise condition used three simultaneous time-reversed speech signals as interferers located at 90 , 180 , and 270. Results indicated that the spatial-filtering algorithm can provide speech reception benefits of 5.8 to 10.7 dB SRT compared to an omni-directional response in a reverberant room with multiple noise sources. Given the observed SRT benefits, coupled with an efficient design, the proposed algorithm is promising as a CI noise-reduction solution.

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Section: E Speech Reception Testingmentioning

confidence: 99%