The effect of word class on speaker-dependent information in the Standard Dutch vowel /aː/

Abstract

Linguistic structure co-determines how a speech sound is produced. This study therefore investigated whether the speaker-dependent information in the vowel [aː] varies when uttered in different word classes. From two spontaneous speech corpora, [aː] tokens were sampled and annotated for word class (content, function word). This was done for 50 male adult speakers of Standard Dutch in face-to-face speech (N = 3,128 tokens), and another 50 male adult speakers in telephone speech (N = 3,136 tokens). First, the effect of word class on various acoustic variables in spontaneous speech was tested. Results showed that [aː]s were shorter and more centralized in function than content words. Next, tokens were used to assess their speaker-dependent information as a function of word class, by using acoustic-phonetic variables to (a) build speaker classification models, and (b) compute the strength-of-evidence, a technique from forensic phonetics. Speaker-classification performance was somewhat better for content than function words, whereas forensic strength-of-evidence was comparable between the word classes. This seems explained by how these methods weigh between-and within-speaker variation. Because these two sources of variation co-varied in size with word class, acoustic word-class variation is not expected to affect the sampling of tokens in forensic speaker comparisons.

Acoustic and speaker variation in Dutch /n/ and /m/ as a function of phonetic context and syllabic position

“…This type of analysis was not used in the current work because of the relatively small number of speakers and because LR models do not allow for the inclusion of interactions with linguistic factors in the modeling of acoustic-phonetic features. It is unclear how the current results would compare to LR speaker classification, but one study reports that small differences in speaker classification obtained with multinomial logistic regression are not maintained in an LR analysis (Heeren, 2020). It was suggested that this may be caused by differences in the weighting of between-and within-speaker variation in these two methods.…”