Liu Chuping, Galvin John, Fu Qian-Jie, Narayanan Shrikanth S
Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA.
J Acoust Soc Am. 2008 May;123(5):2836-47. doi: 10.1121/1.2897047.
In cochlear implants (CIs), different talkers often produce different levels of speech understanding because of the spectrally distorted speech patterns provided by the implant device. A spectral normalization approach was used to transform the spectral characteristics of one talker to those of another talker. In Experiment 1, speech recognition with two talkers was measured in CI users, with and without spectral normalization. Results showed that the spectral normalization algorithm had small but significant effect on performance. In Experiment 2, the effects of spectral normalization were measured in CI users and normal-hearing (NH) subjects; a pitch-stretching technique was used to simulate six talkers with different fundamental frequencies and vocal tract configurations. NH baseline performance was nearly perfect with these pitch-shift transformations. For CI subjects, while there was considerable intersubject variability in performance with the different pitch-shift transformations, spectral normalization significantly improved the intelligibility of these simulated talkers. The results from Experiments 1 and 2 demonstrate that spectral normalization toward more-intelligible talkers significantly improved CI users' speech understanding with less-intelligible talkers. The results suggest that spectral normalization using optimal reference patterns for individual CI patients may compensate for some of the acoustic variability across talkers.
在人工耳蜗（CI）中，由于植入设备提供的频谱失真语音模式，不同的说话者通常会产生不同程度的语音理解。一种频谱归一化方法被用于将一个说话者的频谱特征转换为另一个说话者的频谱特征。在实验1中，在有和没有频谱归一化的情况下，测量了CI使用者对两个说话者的语音识别。结果表明，频谱归一化算法对性能有微小但显著的影响。在实验2中，在CI使用者和正常听力（NH）受试者中测量了频谱归一化的效果；使用了一种音高拉伸技术来模拟六个具有不同基频和声道配置的说话者。对于这些音高偏移变换，NH的基线性能几乎是完美的。对于CI受试者，虽然在不同的音高偏移变换下性能存在相当大的个体间差异，但频谱归一化显著提高了这些模拟说话者的可懂度。实验1和2的结果表明，朝着更易理解的说话者进行频谱归一化显著提高了CI使用者对较难理解的说话者的语音理解。结果表明，为个体CI患者使用最佳参考模式进行频谱归一化可能会补偿不同说话者之间的一些声学变异性。
