Department of Otolaryngology, New York University School of Medicine, New York, New York 10016, USA.
J Acoust Soc Am. 2011 Apr;129(4):2191-200. doi: 10.1121/1.3531806.
The multidimensional phoneme identification model is applied to consonant confusion matrices obtained from 28 postlingually deafened cochlear implant users. This model predicts consonant matrices based on these subjects' ability to discriminate a set of postulated spectral, temporal, and amplitude speech cues as presented to them by their device. The model produced confusion matrices that matched many aspects of individual subjects' consonant matrices, including information transfer for the voicing, manner, and place features, despite individual differences in age at implantation, implant experience, device and stimulation strategy used, as well as overall consonant identification level. The model was able to match the general pattern of errors between consonants, but not the full complexity of all consonant errors made by each individual. The present study represents an important first step in developing a model that can be used to test specific hypotheses about the mechanisms cochlear implant users employ to understand speech.
多维音位识别模型应用于从 28 名后天失聪的人工耳蜗使用者获得的辅音混淆矩阵。该模型基于这些受试者辨别设备呈现给他们的一组假定的频谱、时间和幅度语音线索的能力来预测辅音矩阵。该模型生成的混淆矩阵与个别受试者的辅音矩阵的许多方面相匹配，包括用于语音、方式和位置特征的信息传递，尽管在植入年龄、植入经验、使用的设备和刺激策略以及整体辅音识别水平方面存在个体差异。该模型能够匹配辅音之间的一般错误模式，但不能匹配每个个体所犯的所有辅音错误的全部复杂性。本研究是朝着开发能够用于测试有关人工耳蜗使用者理解言语所采用的机制的具体假设的模型迈出的重要的第一步。
