Faculty Bibliography

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. $$:

Although cochlear implants improve the ability of profoundly deaf children to understand speech, critics claim that the published literature does not document even a single case of a child who has developed a linguistic system based on input from an implant. Thus, it is of clinical and scientific importance to determine whether cochlear implants facilitate the development of English language skills. The English language skills of prelingually deaf children with cochlear implants were measured before and after implantation. We found that the rate of language development after implantation exceeded that expected from unimplanted deaf children (p < .001) and was similar to that of children with normal hearing. Despite a large amount of individual variability, the best performers in the implanted group seem to be developing an oral linguistic system based largely on auditory input obtained from a cochlear implant

A 'multidimensional phoneme identification' (MPI) model is proposed to account for vowel perception by cochlear implant users. A multidimensional extension of the Durlach-Braida model of intensity perception, this model incorporates an internal noise model and a decision model to account separately for errors due to poor sensitivity and response bias. The MPI model provides a complete quantitative description of how listeners encode and combine acoustic cues, and how they use this information to determine which sound they heard. Thus, it allows for testing specific hypotheses about phoneme identification in a very stringent fashion. As an example of the model's application, vowel identification matrices obtained with synthetic speech stimuli (including 'conflicting cue' conditions [Dorman et al., J. Acoust. Soc. Am. 92, 3428-3432 (1992)] were examined. The listeners were users of the 'compressed-analog' stimulation strategy, which filters the speech spectrum into four partly overlapping frequency bands and delivers each signal to one of four electrodes in the cochlea. It was found that a simple model incorporating one temporal cue (i.e., an acoustic cue based only on the time waveforms delivered to the most basal channel) and spectral cues (based on the distribution of amplitudes among channels) can be quite successful in explaining listener responses. The new approach represented by the MPI model may be used to obtain useful insights about speech perception by cochlear implant users in particular, and by all kinds of listeners in general

This study considers the validity of the Words and Gestures and Words and Sentences portions of the MacArthur Communicative Development Inventories (MCDI) for pediatric cochlear implant users who exceed the age ranges for which these inventories were normed. In Experiment 1, scores on the Words and Gestures measures were compared with scores on behavioral receptive and expressive vocabulary and language measures at preimplantation and again at 6 months postimplantation. Children ranged in age from 17 to 72 months, and results revealed significant correlations (r-values:.38-.80), with the strongest correlations resulting between MCDI measures and raw scores derived using the Reynell Developmental Language Scales (RDLS). Correlations also obtained between the number of words produced reported on the MCDI Words and Gestures inventory and the Peabody Picture Vocabulary Test-Third Edition (PPVT-III). Experiment 2 compared scores on the Words and Sentences measures with the same behavioral receptive and expressive vocabulary and language measures at 12 and 18 months postimplantation. Children ranged in age from 38 months to 67 months, and significant correlations obtained between behavioral measures and Words and Sentences measures assessing word production as well as grammatical ability (r-values:.60-.90). The strong validity findings motivated Experiment 3, in which predictive formulas were developed to predict scores on the RDLS based on scores from the MCDI. These models will allow researchers and clinicians to use a single index to assess the language abilities of a broad range of ages and performance abilities within the pediatric cochlear implant population. $$: