An evaluation of a spectral moments metric with voiceless fricative obstruents

Abstract

The classification efficacy of a spectral moments metric was tested on a corpus of voiceless fricatives. The metric classified phonetic identity on the basis of mean, variance, skewness, and kurtosis values derived from cross-sectional spectra. The classification power of both linear- and Bark-based versions of the metric was tested using a corpus of 420 voiceless fricatives (/f/, /θ/, /s/, /∫/, /h/) obtained from multiple talkers and vowel environments. Discriminant function analyses performed on linear and Bark moment profiles of well-identified fricative tokens resulted in overall classification accuracies of 78% and 74%, respectively. Classification accuracies were substantially higher when the nonsibilant (/f/ and /θ/) data were excluded. In an attempt to improve metric classification of nonsibilant tokens, an experiment designed to identify the perceptually appropriate location of a fricative analysis window was performed. The results suggested that nonsibilant classification performance of the metric may be substantially improved when moment information is based upon the spectral information contained within the onset and/or offset (transition) portion of the frication. [Work supported by NINCDS Grant NS19653 and NIDCD Grant DC00219 to SUNY at Buffalo.]

Contributions of Semantic and Facial Information to Perception of Nonsibilant Fricatives

“…A general comparison of the results obtained for fricative perception in quiet (Jongman, 1989;Tomiak, 1990;Balise and Diehl, 1994;Jongman and Wang, submitted) and those obtained by Walden et al (1977) with participants with hearing loss suggests that perception of nonsibilant fricatives in terms of place of articulation is better based on visual information alone than on auditory information alone. However, it should be noted that these auditory and visual studies cannot be directly compared since they differed in the questions they addressed and the methodologies they used.…”

“…The target words were 20 minimal pairs: 10 pairs began with either non-sibilant /f/ or /T/, and 10 pairs began with sibilant /s/ or /S/. This choice of minimal pairs was motivated by previous experiments on fricative perception (e.g., Tomiak, 1990;Balise and Diehl, 1994;Jongman and Wang, submitted). These studies show non-sibilant confusions with non-sibilants and sibilant confusions with sibilants.…”

Acoustic characteristics of Greek fricatives

“…Tomiak (1990) also reported that /h/ displays a greater standard deviation, skewness, and kurtosis than /f/. Shadle and Mair (1996) showed that /S/ is characterized by the lowest spectral mean among the English fricatives.…”

“…Most studies investigating English fricatives have shown that spectral moments can differentiate /S/ from /s/ in terms of spectral mean (e.g., Nittrouer et al, 1989; Nittrouer, 1995;Tjaden and Turner, 1997;McFarland et al, 1996;Jongman et al, 2000), standard deviation (e.g., Tomiak, 1990), skewness (e.g., Nittrouer, 1995;McFarland et al, 1996), and kurtosis (e.g., Tomiak, 1990;Nittrouer, 1995;McFarland et al, 1996). Tomiak (1990) also reported that /h/ displays a greater standard deviation, skewness, and kurtosis than /f/.…”

Acoustic and spectral characteristics of young children’s fricative productions: A developmental perspective

“…In particular, this research has aimed to identify acoustic parameters that might serve to differentiate or discriminate adult productions of stop and fricative consonants in terms of place of articulation. Utilizing spectral moments data as well as more traditional types of acoustic measures, several studies have found that the acoustic signal of adult obstruent productions can be characterized by distinct spectral patterns of acoustic energy ͑e.g., Forrest et al, 1988;Jongman et al, 2000;Tomiak, 1990͒. A second associated area of research has utilized spectral moments analysis to examine how the acoustic properties of stop bursts and/or fricatives change as a function of normal speech development and aging ͑e.g., Forrest et al, 1990Forrest et al, , 1994Miccio, 1996;Nittrouer, 1995;Nittrouer et al, 1989͒. One of the earliest studies to utilize spectral moments data in discriminant classification of obstruents was conducted by Forrest et al ͑1988͒.…”