Modeling spoken word recognition performance by pediatric cochlear implant users using feature identification

Stefan A. Frisch, David Pisoni

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Objective: Computational simulations were carried out to evaluate the appropriateness of several psycholinguistic theories of spoken word recognition for children who use cochlear implants. These models also investigate the interrelations of commonly used measures of closed-set and open-set tests of speech perception. Design: A software simulation of phoneme recognition performance was developed that uses feature identification scores as input. Two simulations of lexical access were developed. In one, early phoneme decisions are used in a lexical search to find the best matching candidate. In the second, phoneme decisions are made only when lexical access occurs. Simulated phoneme and word identification performance was then applied to behavioral data from the Phonetically Balanced Kindergarten test and Lexical Neighborhood Test of open-set word recognition. Simulations of performance were evaluated for children with prelingual sensorineural hearing loss who use cochlear implants with the MPEAK or SPEAK coding strategies. Results: Open-set word recognition performance can be successfully predicted using feature identification scores. In addition, we observed no qualitative differences in performance between children using MPEAK and SPEAK, suggesting that both groups of children process spoken words similarly despite differences in input. Word recognition ability was best predicted in the model in which phoneme decisions were delayed until lexical access. Conclusions: Closed-set feature identification and open-set word recognition focus on different, but related, levels of language processing. Additional insight for clinical intervention may be achieved by collecting both types of data. The most successful model of performance is consistent with current psycholinguistic theories of spoken word recognition. Thus it appears that the cognitive process of spoken word recognition is fundamentally the same for pediatric cochlear implant users and children and adults with normal hearing.

Original languageEnglish
Pages (from-to)578-589
Number of pages12
JournalEar and Hearing
Volume21
Issue number6
StatePublished - 2000

Fingerprint

Cochlear Implants
Pediatrics
Psycholinguistics
Software Design
Speech Perception
Aptitude
Group Processes
Recognition (Psychology)
Sensorineural Hearing Loss
Hearing
Language

ASJC Scopus subject areas

  • Otorhinolaryngology

Cite this

Modeling spoken word recognition performance by pediatric cochlear implant users using feature identification. / Frisch, Stefan A.; Pisoni, David.

In: Ear and Hearing, Vol. 21, No. 6, 2000, p. 578-589.

Research output: Contribution to journalArticle

@article{8f9c057bb7504503a7f75d4c8cdace6f,
title = "Modeling spoken word recognition performance by pediatric cochlear implant users using feature identification",
abstract = "Objective: Computational simulations were carried out to evaluate the appropriateness of several psycholinguistic theories of spoken word recognition for children who use cochlear implants. These models also investigate the interrelations of commonly used measures of closed-set and open-set tests of speech perception. Design: A software simulation of phoneme recognition performance was developed that uses feature identification scores as input. Two simulations of lexical access were developed. In one, early phoneme decisions are used in a lexical search to find the best matching candidate. In the second, phoneme decisions are made only when lexical access occurs. Simulated phoneme and word identification performance was then applied to behavioral data from the Phonetically Balanced Kindergarten test and Lexical Neighborhood Test of open-set word recognition. Simulations of performance were evaluated for children with prelingual sensorineural hearing loss who use cochlear implants with the MPEAK or SPEAK coding strategies. Results: Open-set word recognition performance can be successfully predicted using feature identification scores. In addition, we observed no qualitative differences in performance between children using MPEAK and SPEAK, suggesting that both groups of children process spoken words similarly despite differences in input. Word recognition ability was best predicted in the model in which phoneme decisions were delayed until lexical access. Conclusions: Closed-set feature identification and open-set word recognition focus on different, but related, levels of language processing. Additional insight for clinical intervention may be achieved by collecting both types of data. The most successful model of performance is consistent with current psycholinguistic theories of spoken word recognition. Thus it appears that the cognitive process of spoken word recognition is fundamentally the same for pediatric cochlear implant users and children and adults with normal hearing.",
author = "Frisch, {Stefan A.} and David Pisoni",
year = "2000",
language = "English",
volume = "21",
pages = "578--589",
journal = "Ear and Hearing",
issn = "0196-0202",
publisher = "Lippincott Williams and Wilkins",
number = "6",

}

TY - JOUR

T1 - Modeling spoken word recognition performance by pediatric cochlear implant users using feature identification

AU - Frisch, Stefan A.

AU - Pisoni, David

PY - 2000

Y1 - 2000

N2 - Objective: Computational simulations were carried out to evaluate the appropriateness of several psycholinguistic theories of spoken word recognition for children who use cochlear implants. These models also investigate the interrelations of commonly used measures of closed-set and open-set tests of speech perception. Design: A software simulation of phoneme recognition performance was developed that uses feature identification scores as input. Two simulations of lexical access were developed. In one, early phoneme decisions are used in a lexical search to find the best matching candidate. In the second, phoneme decisions are made only when lexical access occurs. Simulated phoneme and word identification performance was then applied to behavioral data from the Phonetically Balanced Kindergarten test and Lexical Neighborhood Test of open-set word recognition. Simulations of performance were evaluated for children with prelingual sensorineural hearing loss who use cochlear implants with the MPEAK or SPEAK coding strategies. Results: Open-set word recognition performance can be successfully predicted using feature identification scores. In addition, we observed no qualitative differences in performance between children using MPEAK and SPEAK, suggesting that both groups of children process spoken words similarly despite differences in input. Word recognition ability was best predicted in the model in which phoneme decisions were delayed until lexical access. Conclusions: Closed-set feature identification and open-set word recognition focus on different, but related, levels of language processing. Additional insight for clinical intervention may be achieved by collecting both types of data. The most successful model of performance is consistent with current psycholinguistic theories of spoken word recognition. Thus it appears that the cognitive process of spoken word recognition is fundamentally the same for pediatric cochlear implant users and children and adults with normal hearing.

AB - Objective: Computational simulations were carried out to evaluate the appropriateness of several psycholinguistic theories of spoken word recognition for children who use cochlear implants. These models also investigate the interrelations of commonly used measures of closed-set and open-set tests of speech perception. Design: A software simulation of phoneme recognition performance was developed that uses feature identification scores as input. Two simulations of lexical access were developed. In one, early phoneme decisions are used in a lexical search to find the best matching candidate. In the second, phoneme decisions are made only when lexical access occurs. Simulated phoneme and word identification performance was then applied to behavioral data from the Phonetically Balanced Kindergarten test and Lexical Neighborhood Test of open-set word recognition. Simulations of performance were evaluated for children with prelingual sensorineural hearing loss who use cochlear implants with the MPEAK or SPEAK coding strategies. Results: Open-set word recognition performance can be successfully predicted using feature identification scores. In addition, we observed no qualitative differences in performance between children using MPEAK and SPEAK, suggesting that both groups of children process spoken words similarly despite differences in input. Word recognition ability was best predicted in the model in which phoneme decisions were delayed until lexical access. Conclusions: Closed-set feature identification and open-set word recognition focus on different, but related, levels of language processing. Additional insight for clinical intervention may be achieved by collecting both types of data. The most successful model of performance is consistent with current psycholinguistic theories of spoken word recognition. Thus it appears that the cognitive process of spoken word recognition is fundamentally the same for pediatric cochlear implant users and children and adults with normal hearing.

UR - http://www.scopus.com/inward/record.url?scp=0033638012&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033638012&partnerID=8YFLogxK

M3 - Article

VL - 21

SP - 578

EP - 589

JO - Ear and Hearing

JF - Ear and Hearing

SN - 0196-0202

IS - 6

ER -