Picture-naming tasks provide critical data for theories of lexical representation and retrieval and have been performed successfully in sign languages. However, the specific influences of lexical or phonological factors and stimulus properties on sign retrieval are poorly understood. To examine lexical retrieval in American Sign Language (ASL), we conducted a timed picture-naming study using 524 pictures (272 objects and 251 actions). We also compared ASL naming with previous data for spoken English for a subset of 425 pictures. Deaf ASL signers named object pictures faster and more consistently than action pictures, as previously reported for English speakers. Lexical frequency, iconicity, better name agreement, and lower phonological complexity each facilitated naming reaction times (RT)s. RTs were also faster for pictures named with shorter signs (measured by average response duration). Target name agreement was higher for pictures with more iconic and shorter ASL names. The visual complexity of pictures slowed RTs and decreased target name agreement. RTs and target name agreement were correlated for ASL and English, but agreement was lower for ASL, possibly due to the English bias of the pictures. RTs were faster for ASL, which we attributed to a smaller lexicon. Overall, the results suggest that models of lexical retrieval developed for spoken languages can be adopted for signed languages, with the exception that iconicity should be included as a factor. The open-source picture-naming data set for ASL serves as an important, first-of-its-kind resource for researchers, educators, or clinicians for a variety of research, instructional, or assessment purposes.
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A data-driven approach to the semantics of iconicity in American Sign Language and English
abstract A growing body of research shows that both signed and spoken languages display regular patterns of iconicity in their vocabularies. We compared iconicity in the lexicons of American Sign Language (ASL) and English by combining previously collected ratings of ASL signs (Caselli, Sevcikova Sehyr, Cohen-Goldberg, & Emmorey, 2017) and English words (Winter, Perlman, Perry, & Lupyan, 2017) with the use of data-driven semantic vectors derived from English. Our analyses show that models of spoken language lexical semantics drawn from large text corpora can be useful for predicting the iconicity of signs as well as words. Compared to English, ASL has a greater number of regions of semantic space with concentrations of highly iconic vocabulary. There was an overall negative relationship between semantic density and the iconicity of both English words and ASL signs. This negative relationship disappeared for highly iconic signs, suggesting that iconic forms may be more easily discriminable in ASL than in English. Our findings contribute to an increasingly detailed picture of how iconicity is distributed across different languages.
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- Award ID(s):
- 1756403
- NSF-PAR ID:
- 10191872
- Date Published:
- Journal Name:
- Language and Cognition
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 1866-9808
- Page Range / eLocation ID:
- 182 to 202
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The research community generally accepts that signed and spoken languages contain both iconicity and arbitrariness. Iconicity's impact on statistical distributions of motivated forms throughout signed language lexicons is clear (e.g. Occhino, 2016). However, there has been little work to determine whether the iconic links between form and meaning are relevant only to a sign's initial formation, or if these links are stored as part of lexical representations. In the present study, 40 Deaf signers of American Sign Language were asked to rate two-handed signs in their citation form and in one-handed (reduced) forms. Twelve signs were highly iconic. For each of these highly iconic sign, a less iconic but phonologically similar sign of the same grammatical category was also chosen. Signs were presented in carrier sentences and in isolation. Participants preferred one-handed forms of the highly iconic signs over one-handed forms of their phonolgogically similar but less iconic counterparts. Thus, iconicity impacted the application of a synchronic phonological process. This finding suggests that lexical representations retain iconic form-meaning links and that these links are accessible to the phonological grammar.more » « less
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null (Ed.)Abstract Two differences between signed and spoken languages that have been widely discussed in the literature are: the degree to which morphology is expressed simultaneously (rather than sequentially), and the degree to which iconicity is used, particularly in predicates of motion and location, often referred to as classifier predicates. In this paper we analyze a set of properties marking agency and number in four sign languages for their crosslinguistic similarities and differences regarding simultaneity and iconicity. Data from American Sign Language (ASL), Italian Sign Language (LIS), British Sign Language (BSL), and Hong Kong Sign Language (HKSL) are analyzed. We find that iconic, cognitive, phonological, and morphological factors contribute to the distribution of these properties. We conduct two analyses—one of verbs and one of verb phrases. The analysis of classifier verbs shows that, as expected, all four languages exhibit many common formal and iconic properties in the expression of agency and number. The analysis of classifier verb phrases (VPs)—particularly, multiple-verb predicates—reveals (a) that it is grammatical in all four languages to express agency and number within a single verb, but also (b) that there is crosslinguistic variation in expressing agency and number across the four languages. We argue that this variation is motivated by how each language prioritizes, or ranks, several constraints. The rankings can be captured in Optimality Theory. Some constraints in this account, such as a constraint to be redundant, are found in all information systems and might be considered non-linguistic; however, the variation in constraint ranking in verb phrases reveals the grammatical and arbitrary nature of linguistic systems.more » « less
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Perlman, Marcus (Ed.)Longstanding cross-linguistic work on event representations in spoken languages have argued for a robust mapping between an event’s underlying representation and its syntactic encoding, such that–for example–the agent of an event is most frequently mapped to subject position. In the same vein, sign languages have long been claimed to construct signs that visually represent their meaning, i.e., signs that are iconic. Experimental research on linguistic parameters such as plurality and aspect has recently shown some of them to be visually universal in sign, i.e. recognized by non-signers as well as signers, and have identified specific visual cues that achieve this mapping. However, little is known about what makes action representations in sign language iconic, or whether and how the mapping of underlying event representations to syntactic encoding is visually apparent in the form of a verb sign. To this end, we asked what visual cues non-signers may use in evaluating transitivity (i.e., the number of entities involved in an action). To do this, we correlated non-signer judgments about transitivity of verb signs from American Sign Language (ASL) with phonological characteristics of these signs. We found that non-signers did not accurately guess the transitivity of the signs, but that non-signer transitivity judgments can nevertheless be predicted from the signs’ visual characteristics. Further, non-signers cue in on just those features that code event representations across sign languages, despite interpreting them differently. This suggests the existence of visual biases that underlie detection of linguistic categories, such as transitivity, which may uncouple from underlying conceptual representations over time in mature sign languages due to lexicalization processes.more » « less
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null (Ed.)Abstract 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/.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1017/langcog.2019.52
