Department of Hearing and Speech Sciences, University of Maryland-College Park, 0121 Taliaferro Hall, Chapel Drive, College Park, Maryland 20724, USA
Callier Center for Communication Disorders, University of Texas at Dallas, 1966 Inwood Road, Dallas, Texas 75235, USA
J Acoust Soc Am. 2018 Aug;144(2):EL105. doi: 10.1121/1.5049702.
Dynamic spectral shape features accurately classify /t/ and /k/ productions across speakers and contexts. This paper shows that word-initial /t/ and /k/ tokens produced by 21 adults can be differentiated using a single, static spectral feature when spectral energy concentration is considered relative to expectations within a given speaker and vowel context. Centroid and peak frequency-calculated from both acoustic and psychoacoustic spectra-were compared to determine whether one feature could reliably differentiate /t/ and /k/, and, if so, which feature best differentiated them. Centroid frequency from both acoustic and psychoacoustic spectra accurately classified productions of /t/ and /k/.
动态频谱形状特征可准确区分说话人和语境中的 /t/ 和 /k/ 音。本文表明,当考虑到在特定说话人及元音环境下,频谱能量集中与预期值的关系时,21 位成年人所发的词首 /t/ 和 /k/ 音,可通过单一的静态频谱特征加以区分。本文比较了基于声学和心理声学频谱计算的质心频率和峰值频率,以确定是否有一种特征可可靠地区分 /t/ 和 /k/ ,以及如果可以的话,哪种特征能最好地区分它们。基于声学和心理声学频谱的质心频率可准确地对 /t/ 和 /k/ 的发音进行分类。