Verbal fluency is the ability to produce as many words as possible that are either semantically related (e.g. animals, vegetables) or phonologically related (e.g. words that begin with the letter 'L') within one minute. This ability varies based on the person's language proficiency, age of language exposure or whether the person uses one or more languages.

Verbal fluency performance has been widely used as a measure of language proficiency, word retrieval and lexical organization, memory organization, or executive functioning in children and adults in clinical and research settings.

The ability to generate words on the fly has been examined for many spoken languages but it has not been extensively studied in deaf or hearing sign language users with different language backgrounds. How does this ability compare between signed and spoken language? How does the age of exposure to ASL mediate the speed, accuracy, or pattern of sign retrieval?

In one experiment, we examined semantic fluency performance in deaf signers who generated signs in ASL (their dominant language) and compared them with hearing sign-naive monolingual English speakers who produced English words for each of the following categories: 'animals', 'fruits', 'vegetables' and 'clothing'. We found that language, whether spoken or signed, did not influence performance as both signers and speakers retrieved comparable numbers of items, and interestingly, about 30% of the deaf signers' ASL responses were made up of fingerspelling.

In another experiment, we were interested to see if hearing speakers, who are proficient ASL and spoken English, would generate similar numbers of items in both languages. One group of ASL-English bilinguals had deaf parents and used both languages from birth. Another group of ASL-English bilinguals acquired ASL later in adulthood (they were ASL-English interpreters or teachers of the deaf). Semantic fluency scores were higher in English (the dominant language) than ASL (the non-dominant language), regardless of age of ASL acquisition. Again, fingerspelling was relatively common in both groups of signer.

To summarize, modality of the dominant language (spoken or signed) does not affect semantic fluency scores in deaf or hearing adults if fingerspelled forms are considered acceptable responses, and that language dominance rather than age of acquisition affects ASL semantic fluency performance in hearing ASL–English bilinguals 

This study showed that verbal fluency tests are generalizable to signed languages. Semantic fluency is sensitive to language dominance and can be used to measure lexical retrieval in both signed and spoken language modalities. Secondly, this study emphasizes the need to consider fingerspelling when assessing semantic fluency in ASL due to the relatively high occurrence of fingerspelling in ASL responses. This is crucial for clinicians and researchers who are relying on these measures as an index of language proficiency, lexical access or executive functioning. 

Zed Sevcikova Sehyr, Marcel R Giezen, Karen Emmorey (2018). Comparing Semantic Fluency in American Sign Language and English, The Journal of Deaf Studies and Deaf Education, eny013, https://doi.org/10.1093/deafed/eny013

Poster presented at CNS New York Apr 1-4 2016
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We investigated whether hemispheric organization of word and face recognition is uniquely shaped by sign language experience.

For typically developing hearing individuals, learning to read leads to LH-lateralization for words and may trigger subsequent RH-lateralization for faces. Hemispheric specialization for faces in RH may be contingent on prior lateralization for words in LH (Dundas, Plaut & Behrmann, 2014).

Deaf native users of American Sign Language (ASL) have distinct developmental experiences with both words and faces (e.g., the face conveys linguistic information).

What is the relationship between word and face processing for deaf native users of American Sign Language? How do distinct developmental experiences of deaf signers and hearing non-signers affect hemispheric organization for word and face processing? 

In our preliminary report, we report data from 19 hearing non-signers and 23 deaf ASL signers made same-different judgments to pairs of words or faces (192 trials each), where the first stimulus was presented centrally and the second was presented to either the left (LH) or right hemisphere (RH). EEG was recorded to centrally presented words / faces and referenced to the average of all electrode sites. 

In addition, we measured accuracy of discrimination between the central and lateralized words / faces. Based on previous research with hearing non-signers, we expected to observe RH advantage for faces presented in the left visual field and conversely, LH advantage for words presented in the right visual field.

Preliminary ERP results: 
Deaf signers and hearing non-signers showed a similar laterality pattern for N170 to words (left-lateralized) and to faces (bilateral). However, the scalp distributions for the laterality effects differed between the groups and might reflect unique organization of visual pathways in the occipito-temporal cortex for deaf signers.

• Face processing: Deaf and hearing showed a bilateral N170 to faces. Deaf signers showed a slightly right-lateralized response to faces at temporal sites, but behaviorally the hearing non-signers showed a small RH advantage. ERP results suggest perhaps a more distributed circuit for face perception.
• Word processing: Both groups showed a left lateralized N170 response to words, but the asymmetry was somewhat larger for hearing non-signers. At temporal sites, deaf signers exhibited a more bilateral N170 response while hearing non-signers exhibited a strong, left-lateralized N170 response. This result might reflect phonological-orthographic integration in hearing, but not deaf, individuals.

Discrimination accuracy - behavioral results:

• Both groups show higher accuracy for words than faces (F (2, 82) = 29.3)
• LH bias for words but no RH bias for face processing; only hearing group approached significance

Stay tuned for more news and final results!

We investigated how printed and fingerspelled words are coded in short-term memory (STM) for deaf signers. Hearing people recode print into a phonological code for STM, but evidence for phonological coding in deaf readers is mixed. American Sign Language (ASL) also represents orthography with fingerspelling, but it is unclear how fingerspelling is coded in STM. 20 deaf signers and 20 hearing non-signers performed an immediate serial recall task with printed words and another 20 signers with fingerspelled words. Wordlists were manipulated for phonological and manual (fingerspelling) similarity. Both groups displayed a phonological similarity effect for printed words. Deaf signers also showed a phonological similarity effect for fingerspelled words, but there was no manual similarity effect. A follow up study will assess whether a manual similarity effect can be observed with a different similarity metric. Overall, the results suggest that fingerspelling is recoded into a speech-based phonological code in STM.

Sevcikova, Z. & Emmorey, K. (2014) Short-term Memory for Fingerspelling and Print. Paper presented at Center for Research in Language, University of California San Diego. 29 April 2014
http://crl.ucsd.edu/talks/pasttalks.php

Lexical and phonological properties of words, such as frequency and neighborhood density, affect many aspects of language processing. For many spoken languages, there are large databases that can be used to obtain this information, but for American Sign Language (and many other sign languages), no large corpora or normative datasets are currently available. Here we report the development of ASL-LEX, a soon to be publically available resource for sign language researchers, that contains lexical and phonological information for nearly 1,000 ASL signs. We collected subjective frequency ratings for each sign from 25-31 Deaf signers (native and early-exposed) using a 7-point scale (1 = very infrequent). We also collected iconicity ratings for each sign from 21-37 hearing non-signers using a 7-point scale (1 = not at all iconic). In addition, each entry has been coded for phonological features based on a modified version of the Prosodic Model (Brentari, 1998) from which neighborhood densities were calculated. The signs have also been coded for grammatical class and initialization, and the database contains time codes for the sign onset and offset within each video clip. ASL-LEX will soon be accessible online, and users will be able to search the database contents and access the sign videos using pre-defined search criteria.

Our analysis of the subjective frequency data from ASL-LEX reveals a strong correlation between the frequency ratings from native signers and early signers (exposed to ASL before age seven) (rs =.94, p<.001), replicating Mayberry et al. (2014). Thus, subjective frequency ratings are relatively stable across Deaf people who are proficient signers. Subjective frequency ratings for ASL signs (raw scores) were moderately correlated with the word frequencies of their English translations from SUBTLEX (rs =.58, p<.001). We observed a small, but significant correlation between frequency and iconicity (rs =–.17, p<.001), indicating a weak tendency for frequent signs to be rated as less iconic. This pattern is the opposite of that observed by Vinson et al. (2008) for British Sign Language, although they also observed a very weak correlation between subjective frequency and iconicity. Frequency ratings in ASL-LEX were normally distributed, while iconicity ratings were skewed toward the lower end of the scale (median iconicity rating = 2.71). Neighborhood density (ND) correlated weakly with frequency and with iconicity (frequency: rs =.11, p<.001; iconicity: rs =.12, p<.001). For this analysis, ND was defined as the number of sign neighbors sharing three out of four coded features (parallel to the way neighbors have been defined in the spoken language literature, i.e., words that share all but one phoneme). The weak correlation between ND and frequency parallels results from spoken languages (Frauenfelder et al., 1993). Overall, the results indicate weak relationships between iconicity, frequency, and neighborhood density for ASL. Although ASL-LEX is not a substitute for an ASL corpus, this database will be a valuable resource for designing tightly controlled experimental studies, as well as developing assessment and resource materials for education.

Sehyr Sevcikova, Z. Caselli, N. Cohen-Goldberg, A., & Emmorey, K. ASL-LEX: A lexical database of American Sign Language. Poster presented at The 12th Conference on Theoretical Issues in Sign Language Research (TISLR12), Melbourne Convention Centre, Australia, Jan 4-7 2016. Awarded Best Early Award Prize.
Poster abstract here
Poster PDF here

Paper to appear:
Caselli, N., Sehyr Sevcikova, Z., Cohen-Goldberg, A., & Emmorey, K. (2016) ASL-LEX: A lexical database of American Sign Language. Behavior Research Methods.

Please visit our project website:
http://asl-lex.org/

And keep an eye out on the project news here:
https://slhs.sdsu.edu/llcn/asl-lex/