Donai Jeremy J, Paschall D Dwayne
Department of Communication Sciences and Disorders, West Virginia University, P.O. Box 6122, Morgantown, West Virginia 26506.
Texas Tech University Health Sciences Center, Texas Tech University, 3601 4th Street, Lubbock, Texas 79430.
J Acoust Soc Am. 2015 Apr;137(4):1971-82. doi: 10.1121/1.4916195.
Vowels are characteristically described according to low-frequency resonance characteristics, which are presumed to provide the requisite information for identification. Classically, the study of vowel perception has focused on the lowest formant frequencies, typically F1, F2, and F3. Lehiste and Peterson [Phonetica 4, 161-177 (1959)] investigated identification accuracy of naturally produced male vowels composed of various amounts of low- and high-frequency content. Results showed near-chance identification performance for vowel segments containing only spectral information above 3.5 kHz. The authors concluded that high-frequency information was of minor importance for vowel identification. The current experiments report identification accuracy for high-pass filtered vowels produced by two male, two female, and two child talkers using both between- and within-subject designs. Identification performance was found to be significantly above chance for the majority of vowels even after high-pass filtering to remove spectral content below 3.0-3.5 kHz. Additionally, the filtered vowels having the highest fundamental frequency (child talkers) often had the highest identification accuracy scores. Linear discriminant function analysis mirrored perceptual performance when using spectral peak information between 3 and 12 kHz.
元音通常是根据低频共振特性来描述的，这些特性被认为能提供识别所需的信息。传统上，元音感知的研究主要集中在最低共振峰频率上，通常是F1、F2和F3。莱希斯特和彼得森[《语音学》4，161 - 177（1959）]研究了由不同比例的低频和高频成分组成的自然产生的男性元音的识别准确率。结果表明，对于仅包含高于3.5kHz频谱信息的元音片段，识别性能接近随机水平。作者得出结论，高频信息对元音识别的重要性较小。当前的实验报告了使用组间和组内设计，由两名男性、两名女性和两名儿童说话者发出的高通滤波元音的识别准确率。即使在进行高通滤波以去除低于3.0 - 3.5kHz的频谱成分后，大多数元音的识别性能仍显著高于随机水平。此外，基频最高的滤波元音（儿童说话者）通常具有最高的识别准确率得分。当使用3至12kHz之间的频谱峰值信息时，线性判别函数分析反映了感知性能。
