Zhou Ning, Xu Li
School of Hearing, Speech and Language Sciences, Ohio University, Athens, Ohio 45701, USA.
J Acoust Soc Am. 2008 Mar;123(3):1653-64. doi: 10.1121/1.2832623.
The aim of the study was (1) to develop methods for evaluating tone production of children with cochlear implants (CIs) who speak Mandarin Chinese and (2) to evaluate the efficacy of using these methods to assess tone production. The subjects included two groups of native-Mandarin-Chinese-speaking children: 14 prelingually deafened children who had received CIs and 61 normal-hearing (NH) children as controls. The acoustic analysis focused on quantification of the degree of differentiation among lexical tones based on tonal ellipses and the overall similarity of tone contours produced by the children with CIs to normative contours derived from the 61 NH children. An artificial neural network was used to recognize tones produced by the children with CIs after trained with tone tokens produced by the NH children. Finally, perceptual judgments on the tone production of both groups were obtained from eight native-Mandarin-speaking NH adults to evaluate the efficacy of the methods. The results showed that all measures using the acoustic, neural-network, and perceptual analyses were highly correlated with each other and could be used to effectively evaluate tone production of children with CIs.
（1）开发评估使用人工耳蜗（CI）的说普通话儿童声调产出的方法；（2）评估使用这些方法评估声调产出的有效性。研究对象包括两组说普通话的儿童：14名接受人工耳蜗植入的语前聋儿童和61名听力正常（NH）儿童作为对照组。声学分析侧重于基于声调椭圆量化词汇声调之间的差异程度，以及人工耳蜗植入儿童产生的声调轮廓与从61名听力正常儿童得出的标准轮廓的总体相似性。在用听力正常儿童产生的声调样本训练后，使用人工神经网络识别人工耳蜗植入儿童产生的声调。最后，从八位说普通话的听力正常的成年人那里获得了对两组儿童声调产出的感知判断，以评估这些方法的有效性。结果表明，使用声学、神经网络和感知分析的所有测量方法相互之间高度相关，可用于有效评估人工耳蜗植入儿童的声调产出。
