ABSTRACT
This study aimed to determine whether children with cochlear implant in comparison with normal hearing children have delay and disorder in nonverbal skills as well as speech. In addition, whether cochlear implant surgery impact on the progress of these skills. In this study, 60 children under 7 years old both boys and girls were examined via non-random sampling. This group comprises 20 children with cochlear implant [CLs], 20 children with hearing aids [HAs] and 20 age-matched normal hearing children. Communication skills were assessed using the Emory Dyssemia Index which includes verbal, nonverbal and paralinguistic aspects. Moreover, to assess and compare data, ANOVA Variance-analysis and Tukey test were employed. Statistical analysis with an error of less than one percent and significant difference of P<0/000 showed that nonverbal communication skills in hearing impaired children with cochlear implant are better than hearing aid users with severe to profound hearing loss, also in comparison with these children, they have better social communication and act the same as normal hearing children in some skills. By improving their hearing, children can be exposed to social communication and instruction. Therefore, their verbal and nonverbal skills will improve. Also, it is suggested that in a natural manner, parents should expose their hearing impaired children to appropriate verbal and nonverbal stimuli similar to normal hearing children
ABSTRACT
The purpose of this study is to quantify the voice disorders in children with cochlear implantation and hearing aids. Until now, quantifying voice disorders has been done subjectively by speech experts and it is for the first time that the preset study tends to run an objective experiment using signal processing features. 4 levels were considered to be qualify speech. Linear and nonlinear features were extracted from 5 Farsi words: "mashin', "mar', "moosh', "gav" and "mowz" uttered by 30 subjects and then put into hidden Markov classifiers. Classifier outputs then were fused together to have better accuracy. The main hypothesis of the study is to answer this question: Can we separate children into 4 levels based on their voice features? Voice features including "fundamental frequency, first formant, second formant, third formant, first to second formant ratio, third to second formant ratio, Rational Intensity, nasality, approximate entropy and fractal dimension were extracted from speech segments and then are were given to artificial decision making system [classifiers]. The results show that classifiers can separate 4 levels of voice disorders with the accuracy of 93.1%. Among the introduced features, first to second formant ratio and third to second formant ratio can be used directly to track voice recovery after using cochlear implantation or hearing aid. The output of this research study can act as a speaker independent system to help speech specialists with evaluating voice disorder recovery in children who fall in the same range of age