Between-speaker variability in temporal organizations of intensity contours

Abstract

Intensity contours of speech signals were sub-divided into positive and negative dynamics. Positive dynamics were defined as the speed of increases in intensity from amplitude troughs to subsequent peaks, and negative dynamics as the speed of decreases in intensity from peaks to troughs. Mean, standard deviation, and sequential variability were measured for both dynamics in each sentence. Analyses showed that measures of both dynamics were separately classified and between-speaker variability was largely explained by measures of negative dynamics. This suggests that parts of the signal where intensity decreases from syllable peaks are more speaker-specific. Idiosyncratic articulation may explain such results. Abstract: Intensity contours of speech signals were sub-divided into positive and negative dynamics. Positive dynamics were defined as the speed of increases in intensity from amplitude troughs to subsequent peaks, and negative dynamics as the speed of decreases in intensity from peaks to troughs. Mean, standard deviation, and sequential variability were measured for both dynamics in each sentence. Analyses showed that measures of both dynamics were separately classified and betweenspeaker variability was largely explained by measures of negative dynamics. This suggests that parts of the signal where intensity decreases from syllable peaks are more speaker-specific. Idiosyncratic articulation may explain such results.

The distribution of speaker information in Dutch fricatives /s/ and /x/ from telephone dialogues

“…This is sometimes also referred to as variation due to target undershoot. They showed that both intensity dynamics (He & Dellwo, 2017) and formant dynamics (He, Zhang, & Dellwo, 2019) show more between-speaker variation in negative than in positive dynamics. Negative dynamics were defined as the intensity and formant slopes from the syllable's peak to the following trough, which He & Dellwo assume to be the parts of syllables associated with mouth-closing gestures.…”

Development of speech rhythm in first language: The role of syllable intensity variability

“…Moreover, among children groups, OC was significantly smaller than IC in terms of both stdev-I and PVI-I (though the differences between YC and IC/OC were not significant). Given that a strong association exists between the mouth aperture size and the intensity curve, 14,18 one can reasonably argue that the general decrease of intensity variability across an utterance from childhood to adulthood, to a large extent, is a consequence of the decremented inter-lip aperture variability en route to maturation. 25 Further support to this claim is offered by Smith and Zelaznik 28 who investigated how the functional synergies for speech motor coordination developed from children to adults.…”

“…Measuring speech rhythm in terms of intensity variability was motivated by the observed phenomenon that the size of mouth aperture and the signal intensity co-vary: a bigger mouth opening area corresponds to a higher intensity level and vice versa. 14,18 The opening-closing gestures (i.e., the articulatory basis of speech rhythm) constantly change the vocal tract shape, and hence its filter characteristics acting upon the source signal, modifying its spectral properties and the intensity levels as a consequence. Therefore, the opening-closing cycles can be approximated by the signal intensity fluctuations.…”

The dynamics of indexical information in speech: Can recognizability be controlled by the speaker?

“…Idiosyncratic information may also be distributed differently over time. He & Dellwo (2017) showed that within-syllable temporal information leading to the syllable nucleus is less variable compared to the temporal information between nucleus and offsets. They relate this to a lesser amount of articulatory control during the final part of the syllable that may reveal more system specific movement resonances (e.g.…”