Opposing forces on acoustic duration

Tucker, Benjamin V.; Sims, Matthew; Baayen, R. Harald

doi:10.31234/osf.io/jc97w

Cited by 20 publications

(71 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In summary, the more the lexicon as a whole is perturbed, the greater the uncertainty about the targeted lexomes will be. Tucker et al (2019) observed that vowel duration decreased with activation diversity. When uncertainty about the targeted outcome increases, acoustic durations decrease (see also for further examples of shortening under uncertainty Kuperman et al (2007) and Cohen (2014a)).…”

Section: From Ndl To Phonetic Durationsmentioning

confidence: 98%

“…The present study follows up on Tucker et al (2019), who used ndl measures to predict the durations of stem vowels of regular and irregular verbs in English in the Buckeye corpus. Their ndl wide learning network had diphones as cues, and as outcomes both content lexemes (or more specifically, pointers to the meanings of content words) and morphological functions (such as plural or clitic has).…”

Section: From Ndl To Phonetic Durationsmentioning

confidence: 99%

“…The findings by Tucker et al (2019) indicate that speakers have to balance opposing forces during articulation, one that seeks to lengthen parts of the signal in the presence of strong bottom-up support and one that seeks to shorten them in case of high uncertainty.…”

Section: From Ndl To Phonetic Durationsmentioning

confidence: 99%

“…In this paper, we follow up on a study by Tucker et al (2019) which made use of naïve discriminative learning to predict the acoustic duration of the stem vowels of English regular and irregular verbs. Naive discriminative learning uses wide learning networks to study the consequences of error-driven learning for language and language processing.…”

Section: Introductionmentioning

confidence: 99%

“…The study of Tucker et al (2019) calls attention to two opposing forces shaping the duration of verbs' stem vowels. When sublexical and collocational features supported strongly and directly a verbs' tense, this verb's vowel has a longer duration for the majority of data points.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Modeling the Duration of Word-Final S in English with Naive Discriminative Learning

Tomaschek¹,

Ernestus²,

Plag³

2019

Preprint

Self Cite

View full text Add to dashboard Cite

Recent research on the acoustic realization of affixes has revealed differencesbetween phonologically homophonous affixes, for example the different kinds offinal [s] and [z] in English (Plag et al. 2017, Zimmermann 2016). Such resultsare unexpected and unaccounted for in widely-accepted post-Bloomfieldian item-and-arrangement models (Hockett, 1954), which separate lexical and post-lexicalphonology, and in models which interpret phonetic effects as consequences of different prosodic structure. This paper demonstrates that the differences in duration of English final S as a function of the morphological function it expresses (non-morphemic, plural, third person singular, genitive, genitive plural, cliticized has, and cliticized is) can be approximated by considering the support for these morphological functions from the words’ sublexical and collocational properties. We estimated this support using naive discriminative learning, and replicated previous results for English vowels (Tucker et al., 2019) indicating that segment duration is lengthened under higher functional certainty, but shortened under functional uncertainty. We discuss the implications of these results, obtained with wide learning network that eschews representations for morphemes and exponents, for models in theoretical morphology as well as for models of lexical processing.

show abstract

Section: From Ndl To Phonetic Durationsmentioning

confidence: 98%

Section: From Ndl To Phonetic Durationsmentioning

confidence: 99%

Section: From Ndl To Phonetic Durationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modeling the Duration of Word-Final S in English with Naive Discriminative Learning

Tomaschek¹,

Ernestus²,

Plag³

2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Paradigmatic enhancement of stem vowels in regular English inflected verb forms

et al. 2021

View full text Add to dashboard Cite

Many theories of word structure in linguistics and morphological processing in cognitive psychology are grounded in a compositional perspective on the (mental) lexicon in which complex words are built up during speech production from sublexical elements such as morphemes, stems, and exponents. When combined with the hypothesis that storage in the lexicon is restricted to the irregular, the prediction follows that properties specific to regular inflected words cannot co-determine the phonetic realization of these inflected words. This study shows that the stem vowels of regular English inflected verb forms that are more frequent in their paradigm are produced with more enhanced articulatory gestures in the midsaggital plane, challenging compositional models of lexical processing. The effect of paradigmatic probability dovetails well with the Paradigmatic Enhancement Hypothesis and is consistent with a growing body of research indicating that the whole is more than its parts.

show abstract

Stratification effects without morphological strata, syllable counting effects without counts – modelling English stress assignment with Naive Discriminative Learning

2022

View full text Add to dashboard Cite

Stress position in English words is well-known to correlate with both their morphological properties and their phonological organisation in terms of non-segmental, prosodic categories like syllable structure. While two generalisations capturing this correlation, directionality and stratification, are well established, the exact nature of the interaction of phonological and morphological factors in English stress assignment is a much debated issue in the literature. The present study investigates if and how directionality and stratification effects in English can be learned by means of Naive Discriminative Learning, a computational model that is trained using error-driven learning and that does not make any a-priori assumptions about the higher-level phonological organisation and morphological structure of words. Based on a series of simulation studies we show that neither directionality nor stratification need to be stipulated as a-priori properties of words or constraints in the lexicon. Stress can be learned solely on the basis of very flat word representations. Morphological stratification emerges as an effect of the model learning that informativity with regard to stress position is unevenly distributed across all trigrams constituting a word. Morphological affix classes like stress-preserving and stress-shifting affixes are, hence, not predefined classes but sets of trigrams that have similar informativity values with regard to stress position. Directionality, by contrast, emerges as spurious in our simulations; no syllable counting or recourse to abstract prosodic representations seems to be necessary to learn stress position in English.

show abstract

Opposing forces on acoustic duration

Cited by 20 publications

References 67 publications

Modeling the Duration of Word-Final S in English with Naive Discriminative Learning

Modeling the Duration of Word-Final S in English with Naive Discriminative Learning

Paradigmatic enhancement of stem vowels in regular English inflected verb forms

Stratification effects without morphological strata, syllable counting effects without counts – modelling English stress assignment with Naive Discriminative Learning

Contact Info

Product

Resources

About