The road to language learning is not entirely iconic: Iconicity, neighborhood density, and frequency facilitate sign language acquisition

Iconic mappings between words and their meanings are far more prevalent than once estimated, and seem to support children’s acquisition of new words, spoken or signed. We asked whether iconicity’s prevalence in sign language overshadows other factors known to support spoken vocabulary development, including neighborhood density (the number of lexical items phonologically similar to the target), and lexical frequency. Using mixed-effects logistic regressions, we reanalyzed 58 parental reports of native-signing deaf children’s American Sign Language (ASL) productive acquisition of 332 signs (Anderson & Reilly, 2002), and found that iconicity, neighborhood density, and lexical frequency independently facilitated vocabulary acquisition. Despite differences in iconicity and phonological structure, signing children, like children learning a spoken language, track statistical information about lexical items and their phonological properties and leverage them to expand their vocabulary.Research reported in this publication was supported by the National Institute On Deafness And Other Communication Disorders of the National Institutes of Health under Award Number R21DC016104. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work is also supported by a James S. McDonnell Foundation Award to Dr. Jennie Pyers

Deaf children need language, not (just) speech

Deaf and Hard of Hearing (DHH) children need to master at least one language (spoken or signed) to reach their full potential. Providing access to a natural sign language supports this goal. Despite evidence that natural sign languages are beneficial to DHH children, many researchers and practitioners advise families to focus exclusively on spoken language. We critique the Pediatrics article ‘Early Sign Language Exposure and Cochlear Implants’ (Geers et al., 2017) as an example of research that makes unsupported claims against the inclusion of natural sign languages. We refute claims that (1) there are harmful effects of sign language and (2) that listening and spoken language are necessary for optimal development of deaf children. While practical challenges remain (and are discussed) for providing a sign language-rich environment, research evidence suggests that such challenges are worth tackling in light of natural sign languages providing a host of benefits for DHH children – especially in the prevention and reduction of language deprivation.Accepted manuscrip

The ASL-CDI 2.0: an updated, normed adaptation of the MacArthur Bates Communicative Development Inventory for American Sign Language

Vocabulary is a critical early marker of language development. The MacArthur Bates Communicative Development Inventory has been adapted to dozens of languages, and provides a bird’s-eye view of children’s early vocabularies which can be informative for both research and clinical purposes. We present an update to the American Sign Language Communicative Development Inventory (the ASL-CDI 2.0, https://www.aslcdi.org), a normed assessment of early ASL vocabulary that can be widely administered online by individuals with no formal training in sign language linguistics. The ASL-CDI 2.0 includes receptive and expressive vocabulary, and a Gestures and Phrases section; it also introduces an online interface that presents ASL signs as videos. We validated the ASL-CDI 2.0 with expressive and receptive in-person tasks administered to a subset of participants. The norming sample presented here consists of 120 deaf children (ages 9 to 73 months) with deaf parents. We present an analysis of the measurement properties of the ASL-CDI 2.0. Vocabulary increases with age, as expected. We see an early noun bias that shifts with age, and a lag between receptive and expressive vocabulary. We present these findings with indications for how the ASL-CDI 2.0 may be used in a range of clinical and research settingsAccepted manuscrip

From “communication options” to global language proficiency

This work was posted as a Reader Comment in Pediatrics for the article, "Opportunities and Shared Decision-Making to Help Children Who Are Deaf to Communicate" Karl R. White, Louis Z. Cooper, Pediatrics Jun 2017, e20171287; DOI: 10.1542/peds.2017-1287

Operationalization and measurement of sign language

This piece will be included in a collection of commentaries that are being compiled as a Letter to the Editor

An Interactive Visual Database for American Sign Language Reveals How Signs are Organized in the Mind

We are four researchers who study psycholinguistics, linguistics, neuroscience and deaf education. Our team of deaf and hearing scientists worked with a group of software engineers to create the ASL-LEX database that anyone can use for free. We cataloged information on nearly 3,000 signs and built a visual, searchable and interactive database that allows scientists and linguists to work with ASL in entirely new ways

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

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/

American sign language interpreters in public schools: an illusion of inclusion that perpetuates language deprivation

PURPOSE: Many deaf children have limited access to language, spoken or signed, during early childhood – which has damaging effects on many aspects of development. There has been a recent shift to consider deafness and language deprivation as separate but related conditions. As such, educational plans should differentiate between services related to deafness and services related to language deprivation. DESCRIPTION: Many deaf children attend mainstream public schools, and the primary service offered to students who use American Sign Language (ASL) is generally a sign language interpreter. ASSESSMENT: We argue that while sign language interpreters can be an effective accommodation for deafness (i.e., students who are deaf and not language-deprived), there is no reason to believe they are an effective accommodation for language deprivation (i.e., students who are deaf and language-deprived). CONCLUSION: Using interpreters instead of appropriate educational supports may exacerbate symptoms of language deprivation by prolonging the period of time a child goes with limited access to language.Accepted manuscrip

Exploring Strategies for Modeling Sign Language Phonology

Like speech, signs are composed of discrete, recombinable features called phonemes. Prior work shows that models which can recognize phonemes are better at sign recognition, motivating deeper exploration into strategies for modeling sign language phonemes. In this work, we learn graph convolution networks to recognize the sixteen phoneme “types” found in ASL-LEX 2.0. Specifically, we explore how learning strategies like multi-task and curriculum learning can leverage mutually useful information between phoneme types to facilitate better modeling of sign language phonemes. Results on the Sem-Lex Benchmark show that curriculum learning yields an average accuracy of 87% across all phoneme types, outperforming fine-tuning and multi-task strategies for most phoneme types

The development and evaluation of a new ASL text comprehension task

Being able to comprehend a language entails not only mastery of its syntax, lexicon, or phonology, but also the ability to use language to construct meaning, draw inferences, and make connections to world knowledge. However, most available assessments of American Sign Language (ASL) focus on mastery of lower level skills, and as a result little is known about development of higher-order ASL comprehension skills. In this paper, we introduce the American Sign Language Text Comprehension Task (ASL-CMP), a new assessment tool to measure ASL text comprehension ability in deaf children. We first administered the task to a group of deaf children with deaf parents (n = 105, ages 8–18 years) in order to evaluate the reliability and validity of the task, and to develop norms. We found that the ASL-CMP has acceptable levels of internal consistency, difficulty, and discriminability. Next, we administered the task to an additional group of deaf children with hearing parents (n = 251, ages 8–18 years), and found that the ASL-CMP is sensitive to expected patterns: older children have better ASL text comprehension skills, literal questions are generally easier to answer than inferential questions, and children with early exposure to ASL generally outperform those with delayed exposure. We conclude that the ASL-CMP task is reliable and valid and can be used to characterize ASL text comprehension skills in deaf children.https://doi.org/10.3389/fcomm.2020.00025Published versio