Detecting anticipatory effects in speech articulation by means of spectral coefficient analyses

Abstract

Few acoustic studies have attempted to examine anticipatory effects in the earliest part of the release of stop consonants. We investigated the ability of spectral coefficients to reveal anticipatory coarticulation in the burst and early aspiration of stops in monosyllables. Twenty American English speakers produced stop (/k,t,p/) -vowel (/ae,i,o/) -stop (/k,t,p/) sequences in two phrase positions. The first four spectral coefficients (mean, standard deviation, skewness, kurtosis) were calculated for one window centered on the burst of the onset consonant and two subsequent, non-overlapping windows. All coefficients showed an influence of vowel-toconsonant anticipatory coarticulation. Which onset consonant showed the strongest vowel effect depended on the specific coefficient under consideration. A context-dependent consonant-toconsonant anticipatory effect was observed for onset /p/. Findings demonstrate that spectral coefficients can reveal subtle anticipatory adjustments as early as the burst of stop consonants. Different results for the four coefficients suggest that comprehensive spectral analyses offer advantages over other approaches. Studies using these techniques may expose previously unobserved articulatory adjustments among phonetic contexts or speaker populations.

Spectral Coefficient Analyses of Word-Initial Stop Consonant Productions Suggest Similar Anticipatory Coarticulation for Stuttering and Nonstuttering Adults

“…The combination of all four spectral coefficients again proved to be most informative as the aforementioned effects varied in strength across the different coefficients. For example, based on effect size measures, the spectral mean was the most sensitive measure of the Vowel main effect, but the least sensitive measure of the Vowel by Window interaction, a finding that replicates our previous results based on only nonstuttering speakers (Feng et al, 2011).…”

“…In all three analysis windows, and for both groups of participants, the spectral mean was highest for the front vowel /ε/, lower for the central vowel /ʌ/, and lowest for the back vowel /ɔ/. The spectral mean is generally believed to correlate with the size of the cavity in front of an articulatory constriction or obstruction: the longer the anterior cavity, the lower the spectral mean (Feng et al, 2011; Nittrouer, 1995; Stevens, 1998; Tjaden, 2003). Thus, our acoustic results are compatible with a more anterior alveolar tongue tip position when /t/ is articulated before the front vowel /ε/ (shorter anterior cavity, higher spectral mean) and a more posterior alveolar tongue tip position when /t/ is articulated before the back vowel /ɔ/ (longer anterior cavity, lower spectral mean), with an intermediate position before the central vowel /ʌ/ (intermediate cavity length, intermediate spectral mean).…”

“…To measure coarticulation in these two groups of speakers, we calculated the first four coefficients (mean, standard deviation, skewness, and kurtosis) of the acoustic spectrum associated with the production of a perceptually fluent voiceless stop consonant /t/ preceding front, mid, and back vowels in /t/V/k/ words. Specifically, following procedures previously documented to provide a sensitive technique for detecting true anticipatory coarticulation effects (Feng et al, 2011), we calculated the four spectral coefficients for each of three successive 11.61 ms windows, with the first window centered on the burst of the word-initial voiceless stop consonant and the next two windows extending into the aspiration phase of this consonant.…”

“…Here, we applied the analyses described by Feng et al (2011) to compare stuttering and nonstuttering adults with regard to the degree of anticipatory coarticulation in the early part of the release of a voiceless stop consonant. Using a limited but already available data set in which adults who stutter (AWS) and matched adults who do not stutter (AWNS) had produced C 1 VC 2 words, we calculated the first four spectral coefficients for one analysis window centered on the burst of C 1 and two subsequent windows covering the aspiration phase.…”

Nasal Air Emission in Sibilant Fricatives of Cleft Lip and Palate Speech

“…Four spectral moments are explored to observed the spectral deviations. The four spectral moments (mean (M1), standard deviation (M2), skewness (M3) and kurtosis (M4)) are computed from the magnitude spectra of the short-term processed fricative signal [16].…”