Hermes D J
IPO, Center for Research on User-System Interaction, Eindhoven, The Netherlands.
J Speech Lang Hear Res. 1998 Feb;41(1):73-82. doi: 10.1044/jslhr.4101.73.
It has been shown that visual display systems of intonation can be employed beneficially in teaching intonation to persons with deafness and in teaching the intonation of a foreign language. In current training situations the correctness of a reproduced pitch contour is rated either by the teacher or automatically. In the latter case an algorithm mostly estimates the maximum deviation from an example contour. In game-like exercises, for instance, the pupil has to produce a pitch contour within the displayed floor and ceiling of a "tunnel" with a preadjusted height. In an experiment described in the companion paper, phoneticians had rated the dissimilarity of two pitch contours both auditorily, by listening to two resynthesized utterances, and visually, by looking at two pitch contours displayed on a computer screen. A test is reported in which these dissimilarity ratings were compared with automatic ratings obtained with this tunnel measure and with three other measures, the mean distance, the root-mean-square (RMS) distance, and the correlation coefficient. The most frequently used tunnel measure appeared to have the weakest correlation with the ratings by the phoneticians. In general, the automatic ratings obtained with the correlation coefficient showed the strongest correlation with the perceptual ratings. A disadvantage of this measure, however, may be that it normalizes for the range of the pitch contours. If range is important, as in intonation teaching to persons with deafness, the mean distance or the RMS distance are the best physical measures for automatic training of intonation.
研究表明，语调的视觉显示系统可有效地用于向失聪者教授语调以及教授外语的语调。在当前的训练情境中，教师或自动对再现的音高轮廓的正确性进行评级。在后一种情况下，算法大多估计与示例轮廓的最大偏差。例如，在类似游戏的练习中，学生必须在显示的具有预先调整高度的“隧道”的下限和上限内生成音高轮廓。在配套论文中描述的一项实验中，语音学家通过听两个重新合成的话语在听觉上对两个音高轮廓的差异进行评级，并通过查看计算机屏幕上显示的两个音高轮廓在视觉上进行评级。报告了一项测试，其中将这些差异评级与通过这种隧道测量以及其他三种测量方法（平均距离、均方根（RMS）距离和相关系数）获得的自动评级进行了比较。最常用的隧道测量方法似乎与语音学家的评级相关性最弱。一般来说，通过相关系数获得的自动评级与感知评级的相关性最强。然而，这种测量方法的一个缺点可能是它对音高轮廓的范围进行了归一化。如果范围很重要，如在向失聪者教授语调时，平均距离或均方根距离是语调自动训练的最佳物理测量方法。
