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person:svirsm01 or azadpm01 or sagie01 or Nicole Capach (capacn01)

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175


Rationale for early cochlear implanation in congenitally deaf children

Chapter by: Miyamoto RT; Kirk KI; Svirsky MA
in: Cochlear implants : an update by Kubo T; Takahashi Y; Iwaki T [Eds]
The Hague : Kugler, 2002
pp. 329-331
ISBN: 9062991912
CID: 5001

The multidimensional phoneme identification (MPI) model : a new quantitative framework to explain the perception of speech sounds by cochlear implant users

Chapter by: Svirsky MA
in: Methodes d'evaluation des performances de l'implant cochleaire by Sernicalaes W [Eds]
Bruxelles : Universite libre de Bruxelles. Institut des langues vivantes et de phonetique, 2002
pp. 143-186
ISBN: n/a
CID: 5002

Perceptual "vowel spaces" of cochlear implant users: implications for the study of auditory adaptation to spectral shift

Svirsky, M A; Harnsberger, J D; Meyer, T A; Wright, R; Pisoni, D B; Kaiser, A R
Cochlear implant (CI) users differ in their ability to perceive and recognize speech sounds. Two possible reasons for such individual differences may lie in their ability to discriminate formant frequencies or to adapt to the spectrally shifted information presented by cochlear implants, a basalward shift related to the implant's depth of insertion in the cochlea. In the present study, we examined these two alternatives using a method-of-adjustment (MOA) procedure with 330 synthetic vowel stimuli varying in F1 and F2 that were arranged in a two-dimensional grid. Subjects were asked to label the synthetic stimuli that matched ten monophthongal vowels in visually presented words. Subjects then provided goodness ratings for the stimuli they had chosen. The subjects' responses to all ten vowels were used to construct individual perceptual 'vowel spaces.' If CI users fail to adapt completely to the basalward spectral shift, then the formant frequencies of their vowel categories should be shifted lower in both F1 and F2. However, with one exception, no systematic shifts were observed in the vowel spaces of CI users. Instead, the vowel spaces differed from one another in the relative size of their vowel categories. The results suggest that differences in formant frequency discrimination may account for the individual differences in vowel perception observed in cochlear implant users
PMCID:3433712
PMID: 11386565
ISSN: 0001-4966
CID: 67961

Mathematical Studies of the Information in the Stimulus-Response Matrix

Sagi E; Wong W; Norwich KH
This paper considers the information transmitted in absolute judgments as encoded in a stimulus-response matrix (e.g., see Garner and Hake, 1951). When transmitted information is plotted against the number of stimulus categories in the matrix, one obtains a curve that increases monotonically toward a plateau, which is the maximum information transmittable per stimulus for the particular range of stimuli employed. We demonstrate that although the maximum information transmitted is an attribute of the stimulus continuum itself, the shape of the curve is an empirical property of the stimulus-response matrix, which is determined, in part, by maintaining a constant stimulus category width. Therefore, in principle, each curve of information transmitted vs number of stimulus categories can be determined by a single point: the rightmost point on the graph.
PMID: 11178924
ISSN: 0022-2496
CID: 147978

Auditory learning and adaptation after cochlear implantation: a preliminary study of discrimination and labeling of vowel sounds by cochlear implant users

Svirsky, M A; Silveira, A; Suarez, H; Neuburger, H; Lai, T T; Simmons, P M
This study examined two possible reasons underlying longitudinal increases in vowel identification by cochlear implant users: improved labeling of vowel sounds and improved electrode discrimination. The Multidimensional Phoneme Identification (MPI) model was used to obtain ceiling estimates of vowel identification for each subject, given his/her electrode discrimination skills. Vowel identification scores were initially lower than the ceiling estimates, but they gradually approached them over the first few months post-implant. Taken together, the present results suggest that improved labeling is the main mechanism explaining post-implant increases in vowel identification
PMID: 11349792
ISSN: 0001-6489
CID: 67962

Application of the multidimentional phoneme identification (MPI) model to vowel identification in cochlear implant users

Walsh, W.; Svirsky, M.; Kaiser, A.; Neuberger, H.
BIOSIS:PREV200200178947
ISSN: 1081-5589
CID: 97897

Protesis cocleares

Chapter by: Svirsky MA; Loizou PC
in: La coclea : fisiologica y patologia by Velluti R; Suarez H [Eds]
Montevideo : Ediciones Trilce, 2001
pp. 271-305
ISBN: n/a
CID: 5005

Speech intelligibility of prelingually deaf children with multichannel cochlear implants

Svirsky, M A; Sloan, R B; Caldwell, M; Miyamoto, R T
PMID: 11140985
ISSN: 0096-8056
CID: 67965

Language development in children with profound and prelingual hearing loss, without cochlear implants

Svirsky, M A
PMID: 11141026
ISSN: 0096-8056
CID: 97902

Modeling phoneme and open-set word recognition by cochlear implant users: a preliminary report

Meyer, T A; Frisch, S; Svirsky, M A; Pisoni, D B
On the basis of the good predictions for phonemes correct, we conclude that closed-set feature identification may successfully predict phoneme identification in an open-set word recognition task. For word recognition, however, the PCM model underpredicted observed performance, and the addition of a mental lexicon (ie, the SPAMR model) was needed for a good match to data averaged across 7 adults with CIs. The predictions for words correct improved with the addition of a lexicon, providing support for the hypothesis that lexical information is used in open-set spoken word recognition by CI users. The perception of words more complex than CNCs is also likely to require lexical knowledge (Frisch et al, this supplement, pp 60-62) In the future, we will use the performance off individual CI users on psychophysical tasks to generate predicted vowel and consonant confusion matrices to be used to predict open-set spoken word recognition. $$:
PMCID:3429936
PMID: 11141011
ISSN: 0096-8056
CID: 97901