Comparing apples to manzanas and oranges to naranjas: A new measure of English-Spanish vocabulary for dual language learners.

The valid assessment of vocabulary development in dual-language-learning infants is critical to developmental science. We developed the Dual Language Learners English-Spanish (DLL-ES) Inventories to measure vocabularies of U.S. English-Spanish DLLs. The inventories provide translation equivalents for all Spanish and English items on Communicative Development Inventory (CDI) short forms; extended inventories based on CDI long forms; and Spanish language-variety options. Item-Response Theory analyses applied to Wordbank and Web-CDI data (n = 2603, 12-18 months; n = 6722, 16-36 months; half female; 1% Asian, 3% Black, 2% Hispanic, 30% White, 64% unknown) showed near-perfect associations between DLL-ES and CDI long-form scores. Interviews with 10 Hispanic mothers of 18- to 24-month-olds (2 White, 1 Black, 7 multi-racial; 6 female) provide a proof of concept for the value of the DLL-ES for assessing the vocabularies of DLLs.

Expanding the emergentist Account:Reply to open peer commentaries.

Emergentism provides a framework for understanding how language learning processes vary across developmental age and linguistic levels, as shaped by core mechanisms and constraints from cognition, entrenchment, input, transfer, social support, motivation, and neurology. As our commentators all agree, this landscape is marked by intense variability arising from the complexity. These mechanisms interact in collaborative and competitive ways during actual moments of language use. To better understand these interactions and their effects, we need much richer longitudinal data regarding both input and output during actual contexts of usage. We believe that modern technology can eventually provide this data (Flege & Bohn, 2021) in ways that will allow us to more fully populate an emergent landscape.

The Development and Implementation of A Data Repository for Swallow Studies.

PURPOSE: The purpose of this clinical note is to (a) describe the development of an open-source data repository of videofluoroscopic evaluations of swallow studies (VFSS) from individuals across the lifespan with various feeding and swallowing disorders, and (b) to qualitatively assess the usefulness of a repository to engage students in research in swallowing disorders. METHOD: This project was divided into two phases. Phase 1 focused on the development of the repository. This entailed identifying videos, removing private information, developing codes for swallow events and bolus variables, transcribing videos, and uploading them to a publicly available site for easy access. Phase 2 assessed the usefulness of the repository as a research tool. In this phase, a group of graduate and undergraduate students investigated a research question of interest to them. Each phase incorporated a qualitative analysis to examine the challenges encountered in that given phase. RESULTS: An open-source data repository of swallow studies, called DysphagiaBank, was successfully developed and uploaded into the TalkBank data repository. The database was easily employed by both graduate and undergraduates to engage in research in a timely fashion. Across qualitative analysis, the single consistent barrier to success was the COVID-19 pandemic that impacted access to campus and adequate internet for streaming. CONCLUSION: The use of an open-source data repository improved our students abilities to engage in research and enhanced their understanding of swallow physiology across the lifespan.

Collaborative Commentary for Understanding Communication Disorders.

PURPOSE: The goal of the Collaborative Commentary (CC) system is to make the TalkBank adult clinical databases-including AphasiaBank, DementiaBank, RHDBank, and TBIBank-open to commentary and analysis from the full community of researchers, instructors, students, and clinicians. METHOD: CC allows a group leader to establish a commentary group and invite colleagues or students to join as members of the group. Members can then browse through the transcript database using the TalkBank Browser. When they wish to insert a comment, they click on the utterance line number or drag the cursor across a range of utterances and a window opens to receive the comment. The comment can include open text along with codes selected from a predefined set of codes created by that commentary group. RESULTS: CC was released for public use in August 2022. It is being used currently in five research projects and eight classes. An important feature of CC is its ability to evaluate the reliability of coding systems and to sharpen analytic categories. By familiarizing instructors and researchers with the capabilities of CC, we expect to see an increasing usage of CC for a variety of clinical and research applications. CONCLUSIONS: CC can contribute to a better understanding of connected speech features in aphasia, dementia, right hemisphere disorder, and traumatic brain injury. CC represents an extreme innovation not only for the study of adult neurogenic communication disorders but also for the study of spoken language generally.

Automation of Language Sample Analysis.

PURPOSE: A major barrier to the wider use of language sample analysis (LSA) is the fact that transcription is very time intensive. Methods that can reduce the required time and effort could help in promoting the use of LSA for clinical practice and research. METHOD: This article describes an automated pipeline, called Batchalign, that takes raw audio and creates full transcripts in Codes for the Human Analysis of Talk (CHAT) transcription format, complete with utterance- and word-level time alignments and morphosyntactic analysis. The pipeline only requires major human intervention for final checking. It combines a series of existing tools with additional novel reformatting processes. The steps in the pipeline are (a) automatic speech recognition, (b) utterance tokenization, (c) automatic corrections, (d) speaker ID assignment, (e) forced alignment, (f) user adjustments, and (g) automatic morphosyntactic and profiling analyses. RESULTS: For work with recordings from adults with language disorders, six major results were obtained: (a) The word error rate was between 2.4% for controls and 3.4% for patients, (b) utterance tokenization accuracy was at the level reported for speakers without language disorders, (c) word-level diarization accuracy was at 93% for control participants and 83% for participants with language disorders, (d) utterance-level diarization accuracy based on word-level diarization was high, (e) adherence to CHAT format was fully accurate, and (f) human transcriber time was reduced by up to 75%. CONCLUSION: The pipeline dramatically shortens the time gap between data collection and data analysis and provides an output superior to that typically generated by human transcribers.

Age effects in second language acquisition: Expanding the emergentist account.

In 2005, Science magazine designated the problem of accounting for difficulties in L2 (second language) learning as one of the 125 outstanding challenges facing scientific research. A maturationally-based sensitive period has long been the favorite explanation for why ultimate foreign language attainment declines with age-of-acquisition. However, no genetic or neurobiological mechanisms for limiting language learning have yet been identified. At the same time, we know that cognitive, social, and motivational factors change in complex ways across the human lifespan. Emergentist theory provides a framework for relating these changes to variation in the success of L2 learning. The great variability in patterns of learning, attainment, and loss across ages, social groups, and linguistic levels provides the core motivation for the emergentist approach. Our synthesis incorporates three groups of factors which change systematically with age: environmental supports, cognitive abilities, and motivation for language learning. This extended emergentist account explains why and when second language succeeds for some children and adults and fails for others.

Assessment and Therapy Goal Planning Using Free Computerized Language Analysis Software.

Background: We discuss a free software system (Computerized Language Analysis [CLAN]) that can enable fast, thorough, and informative language sample analysis (LSA). Method: We describe methods for eliciting, transcribing, analyzing, and interpreting language samples. Using a hypothetical child speaker, we illustrate use KidEval to generate a diagnostic report. Results: Given LSA results suggestive of expressive language delay, we analyze further using CLAN's Developmental Sentence Score and Index of Productive Syntax routines, and outline the child's use of Brown's morphemes. Discussion: This tutorial provides an introduction to the use of free CLAN software. We discuss how LSA results can be used to structure therapy goals that address specific aspects of grammatical structure that the child may not yet demonstrate in their spoken language. Finally, we provide answers to common questions, including user support.

Communication and Psychosocial Outcomes 2-Years After Severe Traumatic Brain Injury: Development of a Prognostic Model.

OBJECTIVE: To examine predictive factors underlying communication and psychosocial outcomes at 2 years post-injury. Prognosis of communication and psychosocial outcomes after severe traumatic brain injury (TBI) is largely unknown yet is relevant for clinical service provision, resource allocation, and managing patient and family expectations for recovery. DESIGN: A prospective longitudinal inception design was employed with assessments at 3 months, 6 months, and 2 years. PARTICIPANTS: The cohort included 57 participants with severe TBI (N=57). SETTING: Subacute and post-acute rehabilitation. MAIN OUTCOME MEASURES: Preinjury/injury measures included age, sex, education years, Glasgow Coma Scale, and PTA. The 3-month and 6-month data points included speech, language, and communication measures across the ICF domains and measures of cognition. The 2-year outcome measures included conversation, perceived communication skills, and psychosocial functioning. Predictors were examined using multiple regression. INTERVENTIONS: Not applicable. RESULTS: The cognitive and communication measures at 6 months significantly predicted conversation measures at 2 years and psychosocial functioning as reported by others at 2 years. At 6 months, 69% of participants presented with a cognitive-communication disorder (Functional Assessment of Verbal Reasoning and Executive Strategies [FAVRES]). The unique variance accounted for by the FAVRES measure was 7% for conversation measures and 9% for psychosocial functioning. Psychosocial functioning at 2 years was also predicted by pre-injury/injury factors and 3-month communication measures. Pre-injury education level was a unique predictor, accounting for 17% of the variance, and processing speed/memory at 3 months uniquely accounted for 14% of the variance. CONCLUSION: Cognitive-communication skills at 6 months are a potent predictor of persisting communication challenges and poor psychosocial outcomes up to 2 years after a severe TBI. Findings emphasize the importance of addressing modifiable cognitive and communication outcomes variables during the first 2 years after severe TBI to maximize functional patient outcomes.

DementiaBank: Theoretical Rationale, Protocol, and Illustrative Analyses.

PURPOSE: Dementia from Alzheimer's disease (AD) is characterized primarily by a significant decline in memory abilities; however, language abilities are also commonly affected and may precede the decline of other cognitive abilities. To study the progression of language, there is a need for open-access databases that can be used to build algorithms to produce translational models sensitive enough to detect early declines in language abilities. DementiaBank is an open-access repository of transcribed video/audio data from communicative interactions from people with dementia, mild cognitive impairment (MCI), and controls. The aims of this tutorial are to (a) describe the newly established standardized DementiaBank discourse protocol, (b) describe the Delaware corpus data, and (c) provide examples of automated linguistic analyses that can be conducted with the Delaware corpus data and describe additional DementiaBank resources. METHOD: The DementiaBank discourse protocol elicits four types of discourse: picture description, story narrative, procedural, and personal narrative. The Delaware corpus currently includes data from 20 neurotypical adults and 33 adults with MCI from possible AD who completed the DementiaBank discourse protocol and a cognitive-linguistic battery. Language samples were video- and audio-recorded, transcribed, coded, and uploaded to DementiaBank. The protocol materials and transcription programs can be accessed for free via the DementiaBank website. RESULTS: Illustrative analyses show the potential of the Delaware corpus data to help understand discourse metrics at the individual and group levels. In addition, they highlight analyses that could be used across TalkBank's other clinical banks (e.g., AphasiaBank). Information is also included on manual and automatic speech recognition transcription methods. CONCLUSIONS: DementiaBank is a shared online database that can facilitate research efforts to address the gaps in knowledge about language changes associated with MCI and dementia from AD. Identifying early language markers could lead to improved assessment and treatment approaches for adults at risk for dementia.

TBIBank: An International Shared Database to Enhance Research, Teaching and Automated Language Analysis for Traumatic Brain Injury Populations.

Traumatic brain injury (TBI) has been established as a priority research area for public health, affecting an estimated 69 million individuals worldwide each year. Large-scale collaborative datasets may help to better understand this heterogenous and chronic health condition. In this paper, we present TBIBank; an innovative digital health resource that aims to establish a shared database for the study of communication disorders after TBI. We provide an overview of the current database, the standard discourse protocol used for the main TBIBank corpus, and the automated language analyses that can enable diagnostic profiling, comparative evaluation of treatment effects and profiling of recovery patterns. We also highlight the e-learning component of the digital health resource as a research translation tool. We conclude with a discussion of the potential research, clinical, and educational applications of TBIBank and future directions for expanding this digital resource.

Enhancing the Classification of Aphasia: A Statistical Analysis Using Connected Speech.

Background: Large shared databases and automated language analyses allow for the application of new data analysis techniques that can shed new light on the connected speech of people with aphasia (PWA). Aims: To identify coherent clusters of PWA based on language output using unsupervised statistical algorithms and to identify features that are most strongly associated with those clusters. Methods & Procedures: Clustering and classification methods were applied to language production data from 168 PWA. Language samples were from a standard discourse protocol tapping four genres: free speech personal narratives, picture descriptions, Cinderella storytelling, procedural discourse. Outcomes & Results: Seven distinct clusters of PWA were identified by the K-means algorithm. Using the random forests algorithm, a classification tree was proposed and validated, showing 91% agreement with the cluster assignments. This representative tree used only two variables to divide the data into distinct groups: total words from free speech tasks and total closed class words from the Cinderella storytelling task. Conclusion: Connected speech data can be used to distinguish PWA into coherent groups, providing insight into traditional aphasia classifications, factors that may guide discourse research and clinical work.

Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts.

PURPOSE: The aim of this study was to advance the use of structured, monologic discourse analysis by validating an automated scoring procedure for core lexicon (CoreLex) using transcripts. METHOD: Forty-nine transcripts from persons with aphasia and 48 transcripts from persons with no brain injury were retrieved from the AphasiaBank database. Five structured monologic discourse tasks were scored manually by trained scorers and via automation using a newly developed CLAN command based upon previously published lists for CoreLex. Point-to-point (or word-by-word) accuracy and reliability of the two methods were calculated. Scoring discrepancies were examined to identify errors. Time estimates for each method were calculated to determine if automated scoring improved efficiency. RESULTS: Intraclass correlation coefficients for the tasks ranged from .998 to .978, indicating excellent intermethod reliability. Automated scoring using CLAN represented a significant time savings for an experienced CLAN user and for inexperienced CLAN users following step-by-step instructions. CONCLUSIONS: Automated scoring of CoreLex is a valid and reliable alternative to the current gold standard of manually scoring CoreLex from transcribed monologic discourse samples. The downstream time saving of this automated analysis may allow for more efficient and broader utilization of this discourse measure in aphasia research. To further encourage the use of this method, go to https://aphasia.talkbank.org/discourse/CoreLexicon/ for materials and the step-by-step instructions utilized in this project. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.20399304.

Gesture-Speech Integration in Typical and Atypical Adolescent Readers.

This study investigated gesture-speech integration (GSI) among adolescents who are deaf or hard of hearing (DHH) and those with typical hearing. Thirty-eight adolescents (19 with hearing loss) performed a Stroop-like task in which they watched 120 short video clips of gestures and actions twice at random. Participants were asked to press one button if the visual content of the speaker's movements was related to a written word and to press another button if it was unrelated to a written word while accuracy rates and response times were recorded. We found stronger GSI effects among DHH participants than hearing participants. The semantic congruency effect was significantly larger in DHH participants than in hearing participants, and results of our experiments indicated a significantly larger gender congruency effect in DHH participants as compared to hearing participants. Results of this study shed light on GSI among DHH individuals and suggest future avenues for research examining the impact of gesture on language processing and communication in this population.

Attentional Competition and Semantic Integration in Low- and High-Span Readers.

The goal of the current study is to investigate the effects of the distractive textual information on the activation of predictive inference online, and how the readers with high or low working memory capacity (WMC) differ in their online activation and text memory. To test the two hypothesis of attentional competition (AC) and semantic integration (SI), we conducted three experiments to investigate whether a local prediction (e.g., "The vase broke") and a global prediction (e.g., "The wife left her husband"), both of which could be derived from the description of a critical event (e.g., "The angry husband throws the delicate porcelain vase against the brick wall"), are generated in the mind of the reader, and how this generation process is influenced by contextual and cognitive factors of the reader (e.g., working memory capacity). The results of Experiment 1 and 2 suggest that the elaboration of the global aspects in the narrative reduces the local prediction, but makes the global prediction more salient to occur. The evidence from Experiment 3 confirms the hypothesis that even automatic processes are constrained by distant contextual factors, in combination with differences in working memory, and examines how referentially local and global predictions are intertwined in text comprehension. Overall, these data support the immediate integration hypothesis across sentence boundaries at different representation levels (cf. Schmalhofer and Perfetti, 2007), as well as interaction assumptions of different processing levels within referentially local and referentially global processing contexts (cf. Yang et al., 2005).

Precision rehabilitation for aphasia by patient age, sex, aphasia severity, and time since stroke? A prespecified, systematic review-based, individual participant data, network, subgroup meta-analysis.

BACKGROUND: Stroke rehabilitation interventions are routinely personalized to address individuals' needs, goals, and challenges based on evidence from aggregated randomized controlled trials (RCT) data and meta-syntheses. Individual participant data (IPD) meta-analyses may better inform the development of precision rehabilitation approaches, quantifying treatment responses while adjusting for confounders and reducing ecological bias. AIM: We explored associations between speech and language therapy (SLT) interventions frequency (days/week), intensity (h/week), and dosage (total SLT-hours) and language outcomes for different age, sex, aphasia severity, and chronicity subgroups by undertaking prespecified subgroup network meta-analyses of the RELEASE database. METHODS: MEDLINE, EMBASE, and trial registrations were systematically searched (inception-Sept2015) for RCTs, including ⩾ 10 IPD on stroke-related aphasia. We extracted demographic, stroke, aphasia, SLT, and risk of bias data. Overall-language ability, auditory comprehension, and functional communication outcomes were standardized. A one-stage, random effects, network meta-analysis approach filtered IPD into a single optimal model, examining SLT regimen and language recovery from baseline to first post-intervention follow-up, adjusting for covariates identified a-priori. Data were dichotomized by age (⩽/> 65 years), aphasia severity (mild-moderate/ moderate-severe based on language outcomes' median value), chronicity (⩽/> 3 months), and sex subgroups. We reported estimates of means and 95% confidence intervals. Where relative variance was high (> 50%), results were reported for completeness. RESULTS: 959 IPD (25 RCTs) were analyzed. For working-age participants, greatest language gains from baseline occurred alongside moderate to high-intensity SLT (functional communication 3-to-4 h/week; overall-language and comprehension > 9 h/week); older participants' greatest gains occurred alongside low-intensity SLT (⩽ 2 h/week) except for auditory comprehension (> 9 h/week). For both age-groups, SLT-frequency and dosage associated with best language gains were similar. Participants ⩽ 3 months post-onset demonstrated greatest overall-language gains for SLT at low intensity/moderate dosage (⩽ 2 SLT-h/week; 20-to-50 h); for those > 3 months, post-stroke greatest gains were associated with moderate-intensity/high-dosage SLT (3-4 SLT-h/week; ⩾ 50 hours). For moderate-severe participants, 4 SLT-days/week conferred the greatest language gains across outcomes, with auditory comprehension gains only observed for ⩾ 4 SLT-days/week; mild-moderate participants' greatest functional communication gains were associated with similar frequency (⩾ 4 SLT-days/week) and greatest overall-language gains with higher frequency SLT (⩾ 6 days/weekly). Males' greatest gains were associated with SLT of moderate (functional communication; 3-to-4 h/weekly) or high intensity (overall-language and auditory comprehension; (> 9 h/weekly) compared to females for whom the greatest gains were associated with lower-intensity SLT (< 2 SLT-h/weekly). Consistencies across subgroups were also evident; greatest overall-language gains were associated with 20-to-50 SLT-h in total; auditory comprehension gains were generally observed when SLT > 9 h over ⩾ 4 days/week. CONCLUSIONS: We observed a treatment response in most subgroups' overall-language, auditory comprehension, and functional communication language gains. For some, the maximum treatment response varied in association with different SLT-frequency, intensity, and dosage. Where differences were observed, working-aged, chronic, mild-moderate, and male subgroups experienced their greatest language gains alongside high-frequency/intensity SLT. In contrast, older, moderate-severely impaired, and female subgroups within 3 months of aphasia onset made their greatest gains for lower-intensity SLT. The acceptability, clinical, and cost effectiveness of precision aphasia rehabilitation approaches based on age, sex, aphasia severity, and chronicity should be evaluated in future clinical RCTs.

Dynamic Norming and Open Science.

In a recent issue of JSLHR, Tucci et al. (2022) presented a method for assigning SEM scores to a language sample. However, this method is based on data that are not publicly available and uses a commercial analysis program that is not open source. The TalkBank system and the Child Language Data Exchange System database provides free analysis software based on openly accessible data, thereby adhering to Open Science standards, which represent an important next step for the fields of speech and hearing.

The Effects of Right Hemisphere Brain Damage on Question-Asking in Conversation.

BACKGROUND: Right hemisphere brain damage (RHD) can cause challenges with information gathering. Cognitive processes aid in implicit and explicit information gathering, yet the relationship between these processes and question-asking, the most explicit avenue of information gathering, has not been explored. The purpose of this exploratory descriptive study was to test the hypothesis that adults with RHD differ from controls in the types of questions produced during a conversational discourse task and whether observed differences are associated with cognitive limitations. METHOD: Adults with RHD (n = 15) and controls (n = 15) participated in a 5-min "first-encounter conversation" and were assessed for attention, memory, executive functioning (EF), visuospatial skills, and language domains using the Cognitive Linguistic Quick Test (CLQT). Questions produced during the conversation were coded and tallied by type: polar (yes/no), content (wh-), or alternative (A or B) using Computerized Language Analysis programs. Groups were compared on total questions used, use of questions by type, and CLQT domain scores; associations were computed between cognitive domain scores and question types. RESULTS: Compared with controls, adults with RHD used half as many questions overall and scored significantly lower on the attention, executive function, and visuospatial domains of the CLQT. For the RHD group, there was a significant correlation between EF scores and the production of content and polar questions. CONCLUSIONS: The frequency of question-asking is important to understanding the communication profile in adults with RHD. Executive function, attention, and, to a lesser extent, visuospatial capabilities may contribute to question-asking behaviors in conversation in this population. The RHD Framework for Asking Questions is proposed to illustrate the potential areas of deficit in the question-asking process after RHD.

Evaluating Voice-Assistant Commands for Dementia Detection.

Early detection of cognitive decline involved in Alzheimer's Disease and Related Dementias (ADRD) in older adults living alone is essential for developing, planning, and initiating interventions and support systems to improve users' everyday function and quality of life. In this paper, we explore the voice commands using a Voice-Assistant System (VAS), i.e., Amazon Alexa, from 40 older adults who were either Healthy Control (HC) participants or Mild Cognitive Impairment (MCI) participants, age 65 or older. We evaluated the data collected from voice commands, cognitive assessments, and interviews and surveys using a structured protocol. We extracted 163 unique command-relevant features from each participant's use of the VAS. We then built machine-learning models including 1-layer/2-layer neural networks, support vector machines, decision tree, and random forest, for classification and comparison with standard cognitive assessment scores, e.g., Montreal Cognitive Assessment (MoCA). Our classification models using fusion features achieved an accuracy of 68%, and our regression model resulted in a Root-Mean-Square Error (RMSE) score of 3.53. Our Decision Tree (DT) and Random Forest (RF) models using selected features achieved higher classification accuracy 80-90%. Finally, we analyzed the contribution of each feature set to the model output, thus revealing the commands and features most useful in inferring the participants' cognitive status. We found that features of overall performance, features of music-related commands, features of call-related commands, and features from Automatic Speech Recognition (ASR) were the top-four feature sets most impactful on inference accuracy. The results from this controlled study demonstrate the promise of future home-based cognitive assessments using Voice-Assistant Systems.

The Index of Productive Syntax: Psychometric Properties and Suggested Modifications.

PURPOSE: The Index of Productive Syntax (IPSyn) is a well-known language sample analysis tool. However, its psychometric properties have not been assessed across a wide sample of typically developing preschool-age children and children with language disorders. We sought to determine the profile of IPSyn scores by age over early childhood. We additionally explored whether the IPSyn could be shortened to fewer items without loss of information and whether the required language sample could be shortened from a current required number of 100 utterances to 50. METHOD: We used transcripts from the Child Language Data Exchange System, including 1,051 samples of adult-child conversational play with toys within the theoretical framework of item response theory. Samples included those from typically developing children as well as children with hearing loss, Down syndrome, and late language emergence. RESULTS: The Verb Phrase and Sentence Structure subscales showed more stable developmental trajectories over the preschool years and greater differentiation between typical and atypical cohorts than did the Noun Phrase and Question/Negation subscales. A number of current IPSyn scoring items can be dropped without loss of information, and 50-utterance samples demonstrate most of the same psychometric properties of longer samples. DISCUSSION: Our findings suggest ways in which the IPSyn can be automated and streamlined (proposed IPSyn-C) so as to provide useful clinical guidance with fewer items and a shorter required language sample. Reference values for the IPSyn-C are provided. Trajectories for one subscale (Question/Negation) appear inherently unstable and may require structured elicitation. Potential limitations, ramifications, and future directions are discussed. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.16915690.