Sign Language Phonology

Brentari, Diane

doi:10.1017/9781316286401

Cited by 41 publications

(18 citation statements)

References 403 publications

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“…Neither of these examples involve anything like the robust interaction of features in spoken languages at the sublexical level in assimilation (spreading) or dissimilation. We do, however, find spreading of manual features with respect to morphologically complex lexical items, such as roots with affixes (Sandler, Aronoff, Meir, & Padden, 2011) and compounds (Brentari, 2019, especially section 8.3). As a compound becomes lexicalized (conventionalized), a given parameter (such as handshape, orientation, or both) can spread across both compound elements without affecting or being affected by the other parameters of the compound elements 9 , 10 .…”

Section: Background On Phonological Parameter Interactionscontrasting

confidence: 56%

“…While a number of models have been proposed for the representation and organization of sign language phonology, each parameter in general is taken to involve pretty much the same features, which are largely (but not entirely) discrete from one parameter to the next (Brentari, 1998(Brentari, , 2019Sandler, 2012a). The movement parameter has a path with beginning and end, shape and direction, iteration or not, and dynamics.…”

Section: Phonological Parametersmentioning

confidence: 99%

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Correlations Between Handshape and Movement in Sign Languages

Napoli

Ferrara²

2021

Cognitive Science

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Sign language phonological parameters are somewhat analogous to phonemes in spoken language. Unlike phonemes, however, there is little linguistic literature arguing that these parameters interact at the sublexical level. This situation raises the question of whether such interaction in spoken language phonology is an artifact of the modality or whether sign language phonology has not been approached in a way that allows one to recognize sublexical parameter interaction. We present three studies in favor of the latter alternative: a shape-drawing study with deaf signers from six countries, an online dictionary study of American Sign Language, and a study of selected lexical items across 34 sign languages. These studies show that, once iconicity is considered, handshape and movement parameters interact at the sublexical level. Thus, consideration of iconicity makes transparent similarities in grammar across both modalities, allowing us to maintain certain key findings of phonological theory as evidence of cognitive architecture.

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Section: Background On Phonological Parameter Interactionscontrasting

confidence: 56%

Section: Phonological Parametersmentioning

confidence: 99%

Correlations Between Handshape and Movement in Sign Languages

Napoli

Ferrara²

2021

Cognitive Science

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“…First, the four phonological variables (two measures of ND, Phonotactic Probability, and Phonological Complexity) were by definition expected to be correlated ( Table 2 ). While each of these measures was motivated by a different theory and body of literature (for a review, see Brentari, 2019 ), the way they were each calculated was highly interdependent as all three measures were determined in part by the probability of phonological features. Phonotactic probability does this in the most straightforward way, as it reflects the frequency of a sign’s features within the language.…”

Section: Resultsmentioning

confidence: 99%

The ASL-LEX 2.0 Project: A Database of Lexical and Phonological Properties for 2,723 Signs in American Sign Language

Sehyr

Caselli

Cohen-Goldberg

et al. 2021

The Journal of Deaf Studies and Deaf Education

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ASL-LEX is a publicly available, large-scale lexical database for American Sign Language (ASL). We report on the expanded database (ASL-LEX 2.0) that contains 2,723 ASL signs. For each sign, ASL-LEX now includes a more detailed phonological description, phonological density and complexity measures, frequency ratings (from deaf signers), iconicity ratings (from hearing non-signers and deaf signers), transparency (“guessability”) ratings (from non-signers), sign and videoclip durations, lexical class, and more. We document the steps used to create ASL-LEX 2.0 and describe the distributional characteristics for sign properties across the lexicon and examine the relationships among lexical and phonological properties of signs. Correlation analyses revealed that frequent signs were less iconic and phonologically simpler than infrequent signs and iconic signs tended to be phonologically simpler than less iconic signs. The complete ASL-LEX dataset and supplementary materials are available at https://osf.io/zpha4/ and an interactive visualization of the entire lexicon can be accessed on the ASL-LEX page: http://asl-lex.org/.

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“…For example, the handshape of KNOWbb ( Figure 1A ) can be described in terms of its selected fingers (all fingers selected), joint position (selected fingers extended), and thumb position (extended). Several models have been proposed to account for the possible patterns observed for hand configurations ( Sandler, 1989 ; Corina and Sandler, 1993 ; van der Hulst, 1993 ; van der Kooij, 2002 ; Sandler and Lillo-Martin, 2006 ), and some models have also adopted more complex representations for other parameters (movement, location, and orientation) ( Brentari, 1998 , 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…Phonological complexity of individual signs can be defined in various ways ( Mann et al, 2010 ; Ortega and Morgan, 2015 ; Brentari, 2019 ; Morgan et al, 2019 ; van der Hulst and van der Kooij, 2021 ). For example, some signs use one hand (e.g., the three signs illustrated in Figure 1 ), while others use both hands (e.g., ALL-DAY and ANNOTATE).…”

Section: Introductionmentioning

confidence: 99%

Phonological development in American Sign Language-signing children: Insights from pseudosign repetition tasks

Pichler²,

Kozak³

et al. 2022

Front. Psychol.

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In this study, we conducted a pseudosign (nonce sign) repetition task with 22 children (mean age: 6;04) acquiring American Sign Language (ASL) as a first language (L1) from deaf parents. Thirty-nine pseudosigns with varying complexity were developed and organized into eight categories depending on number of hands, number of simultaneous movement types, and number of movement sequences. Pseudosigns also varied in handshape complexity. The children’s performance on the ASL pseudosign task improved with age, displaying relatively accurate (re)production of location and orientation, but much less accurate handshape and movement, a finding in line with real sign productions for both L1 and L2 signers. Handshapes with higher complexity were correlated with lower accuracy in the handshape parameter. We found main effects of sequential and simultaneous movement combinations on overall performance. Items with no movement sequence were produced with higher overall accuracy than those with a movement sequence. Items with two simultaneous movement types or a single movement type were produced with higher overall accuracy than those with three simultaneous movement types. Finally, number of hands did not affect the overall accuracy. Remarkably, movement sequences impose processing constraints on signing children whereas complex hands (two hands) and two simultaneous movement types do not significantly lower accuracy, indicating a capacity for processing multiple simultaneous components in signs. Spoken languages, in contrast, manifest greater complexity in temporal length. Hearing children’s pseudoword repetition still displays high levels of accuracy on disyllabic words, with complexity effects affecting only longer multisyllabic words. We conclude that the pseudosign repetition task is an informative tool for studies of signing children’s phonological development and that sheds light on potential modality effects for phonological development.

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Sign Language Phonology

Cited by 41 publications

References 403 publications

Correlations Between Handshape and Movement in Sign Languages

Correlations Between Handshape and Movement in Sign Languages

The ASL-LEX 2.0 Project: A Database of Lexical and Phonological Properties for 2,723 Signs in American Sign Language

Phonological development in American Sign Language-signing children: Insights from pseudosign repetition tasks

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