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Speech recognition at simulated soft, conversational, and raised-to-loud vocal efforts by adults with cochlear implants

 

作者: Margaret W. Skinner,   Laura K. Holden,   Timothy A. Holden,   Marilyn E. Demorest,   Marios S. Fourakis,  

 

期刊: The Journal of the Acoustical Society of America  (AIP Available online 1997)
卷期: Volume 101, issue 6  

页码: 3766-3782

 

ISSN:0001-4966

 

年代: 1997

 

DOI:10.1121/1.418383

 

出版商: Acoustical Society of America

 

数据来源: AIP

 

摘要:

Ten postlinguistically deaf adults who used the Nucleus Cochlear Implant System and SPEAK speech coding strategy responded to vowels, consonants, words, and sentences presented sound-only at 70, 60, and 50 dB sound-pressure level. Highest group mean scores were at a raised-to-loud level of 70 dB for consonants (73%), words (44%), and sentences (87%); the highest score for vowels (70%) was at a conversational level of 60 dB. Lowest group mean scores were at a soft level of 50 dB for vowels (56%), consonants (47%), words (10%), and sentences (29%); all except subject 7 had some open-set speech recognition at this level. For the conversational level (60 dB), group mean scores for sentences and words were 72% and 29%, respectively. With this performance and sound-pressure level, it was observed that these subjects communicated successfully in a variety of listening situations. Given these subjects’ speech recognition scores at 60 dB and the fact that 70 dB does not simulate the vocal effort used in everyday speaking situations, it is suggested that cochlear implant candidates and implantees be evaluated with speech tests presented at 60 dB instead of the customary 70 dB sound-pressure level to simulate benefit provided by implants in everyday life. Analysis of individuals’ scores at the three levels for the four speech materials revealed different patterns of speech recognition among subjects (e.g., subjects 1 and 5). Future research on the relation between stimuli, sound processing, and subjects’ responses associated with these different patterns may provide guidelines to select parameter values with which to map incoming sound onto an individual’s electrical dynamic range between threshold and maximum acceptable loudness level to improve speech recognition.

 

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