Gordon P C, Keyes L, Yung Y F
Department of Psychology, University of North Carolina, Chapel Hill, NC 27599-3270, USA.
Percept Psychophys. 2001 May;63(4):746-58. doi: 10.3758/bf03194435.
The perception of the distinction between /r/ and /l/ by native speakers of American English and of Japanese was studied using natural and synthetic speech. The American subjects were all nearly perfect at recognizing the natural speech sounds, whereas there was substantial variation among the Japanese subjects in their accuracy of recognizing /r/ and /l/ except in syllable-final position. A logit model, which additively combined the acoustic information conveyed by F1-transition duration and by F3-onset frequency, provided a good fit to the perception of synthetic /r/ and /l/ by the American subjects. There was substantial variation among the Japanese subjects in whether the F1 and F3 cues had a significant effect on their classifications of the synthetic speech. This variation was related to variation in accuracy of recognizing natural /r/ and /l/, such that greater use of both the F1 cue and the F3 cue in classifying the synthetic speech sounds was positively related to accuracy in recognizing the natural sounds. However, multiple regression showed that use of the F1 cue did not account for significant variance in natural speech performance beyond that accounted for by the F3 cue, indicating that the F3 cue is more important than the F1 cue for Japanese speakers learning English. The relation between performance on natural and synthetic speech also provides external validation of the logit model by showing that it predicts performance outside of the domain of data to which it was fit.
使用自然语音和合成语音，研究了以美式英语为母语者和以日语为母语者对/r/和/l/区别的感知。美国受试者在识别自然语音方面几乎都表现完美，而日本受试者在识别/r/和/l/时，除了音节末尾位置外，准确率存在很大差异。一个逻辑模型将F1过渡时长和F3起始频率所传达的声学信息相加组合，很好地拟合了美国受试者对合成/r/和/l/的感知。在F1和F3线索对日本受试者合成语音分类是否有显著影响方面，存在很大差异。这种差异与识别自然/r/和/l/的准确率差异有关，即在对合成语音进行分类时更多地使用F1线索和F3线索与识别自然语音的准确率呈正相关。然而，多元回归表明，使用F1线索并不能解释自然语音表现中超出F3线索所解释的显著方差，这表明对于学习英语的日语使用者来说，F3线索比F1线索更重要。自然语音和合成语音表现之间的关系还通过表明该逻辑模型能够预测其拟合数据范围之外的表现，为该模型提供了外部验证。
