Insights From Important Event Recounts Told by People With Traumatic Brain Injury.

PURPOSE: Communication can be chronically impacted by severe traumatic brain injury (TBI), yet there is a critical lack of research investigating communication recovery beyond 12 months postinjury with discourse measures. This longitudinal study aimed to investigate quantitative and qualitative changes in important event recounts produced by a group of people with severe TBI up to 2 years postinjury. METHOD: A prospective observational design with an inception cohort was adopted. Thirty-four participants with severe TBI were asked to produce an important event recount at 6, 12, and 24 months postinjury. A mixed-methods approach comprised a quantitative analysis of microlinguistic and macrostructural measures, using the automated discourse command EVAL in Computerized Language Analysis (CLAN) and the CLAN Collaborative Commentary tool, respectively. Statistical analysis included a repeated-measures analysis of variance and the Friedman test. An independent qualitative content analysis was also conducted. RESULTS: The measures revealed significant differences between 6 and 24 months, indicating a protracted recovery trajectory. The microlinguistic analysis showed increased use of revision and repetition over time. The macrostructural analysis indicated changes with orientation to recount characters, evaluative comments, and the number of events or complexity of the recount. The content analysis revealed categories of (a) childhood events, (b) family and relationships, (c) career and education, and (d) grief and loss. Topics at 6 months focused on childhood events and holidays, whereas career and education predominated at 24 months. CONCLUSIONS: This is the first study to explore important event recounts told by people with severe TBI as they recovered. Participants showed discourse recovery beyond 12 months, highlighting the need for equivalent timing of service provision. The important event recount shows good potential as an ecologically valid assessment tool to evaluate communication recovery that can also be integrated with advances in computerized analysis. Analyses additionally provided insights into potential therapy targets and content categories for chronic discourse impairments. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.26499271.

The Great Communicator: Audrey Holland's Legacy and Lessons.

Audrey Holland's core beliefs of respect for people and the quality of their lives informed her life's work. This examination of the ways she managed the academic, research, and clinical parts of her illustrious career shows how Audrey leaves a rich legacy and serves as a model for navigating an impactful career path and enhancing clinical interactions. First, she mentored more than 30 doctoral students who then mentored further generations of students, ran clinics, or shaped policy. She also regularly taught classes, supervised student clinicians, and traveled the world doing lectures and workshops. Second, her scholarship spanned more than 50 years and a range of subjects, such as assessment and treatment, self-determination and self-advocacy, pragmatics, counseling, coaching, and communication strategies. Third, her collaborations with many colleagues within the field and in related fields extended her impact even further. Finally, a close analysis of her clinical communication style shows how Audrey's simple, nonverbal behaviors (e.g., eye contact, body position) brought out the best in the people with whom she worked. On all these levels-mentorship, scholarship, collaboration, and communication style-Audrey's legacy leaves a vast array of powerful lessons that can be studied, emulated, and appreciated for years to come.

The Case of the Cookie Jar: Differences in Typical Language Use in Dementia.

Background: Findings from language sample analyses can provide efficient and effective indicators of cognitive impairment in older adults. Objective: This study used newly automated core lexicon analyses of Cookie Theft picture descriptions to assess differences in typical use across three groups. Methods: Participants included adults without diagnosed cognitive impairments (Control), adults diagnosed with Alzheimer's disease (ProbableAD), and adults diagnosed with mild cognitive impairment (MCI). Cookie Theft picture descriptions were transcribed and analyzed using CLAN. Results: Results showed that the ProbableAD group used significantly fewer core lexicon words overall than the MCI and Control groups. For core lexicon content words (nouns, verbs), however, both the MCI and ProbableAD groups produced significantly fewer words than the Control group. The groups did not differ in their use of core lexicon function words. The ProbableAD group was also slower to produce most of the core lexicon words than the MCI and Control groups. The MCI group was slower than the Control group for only two of the core lexicon content words. All groups mentioned a core lexicon word in the top left quadrant of the picture early in the description. The ProbableAD group was then significantly slower than the other groups to mention a core lexicon word in the other quadrants. Conclusions: This standard and simple-to-administer task reveals group differences in overall core lexicon scores and the amount of time until the speaker produces the key items. Clinicians and researchers can use these tools for both early assessment and measurement of change over time.

An Overview of the ADReSS-M Signal Processing Grand Challenge on Multilingual Alzheimer's Dementia Recognition Through Spontaneous Speech.

The ADReSS-M Signal Processing Grand Challenge was held at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023. The challenge targeted difficult automatic prediction problems of great societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD) and the estimation of cognitive test scoress. Participants were invited to create models for the assessment of cognitive function based on spontaneous speech data. Most of these models employed signal processing and machine learning methods. The ADReSS-M challenge was designed to assess the extent to which predictive models built based on speech in one language generalise to another language. The language data compiled and made available for ADReSS-M comprised English, for model training, and Greek, for model testing and validation. To the best of our knowledge no previous shared research task investigated acoustic features of the speech signal or linguistic characteristics in the context of multilingual AD detection. This paper describes the context of the ADReSS-M challenge, its data sets, its predictive tasks, the evaluation methodology we employed, our baseline models and results, and the top five submissions. The paper concludes with a summary discussion of the ADReSS-M results, and our critical assessment of the future outlook in this field.

Automated Analysis of Fluency Behaviors in Aphasia.

PURPOSE: This study explored the use of an automated language analysis tool, FLUCALC, for measuring fluency in aphasia. The purpose was to determine whether CLAN's FLUCALC command could produce efficient, objective outcome measures for salient aspects of fluency in aphasia. METHOD: The FLUCALC command was used on CHAT transcripts of Cinderella stories from people with aphasia (PWA; n = 281) and controls (n = 257) in the AphasiaBank database. RESULTS: PWA produced significantly fewer total words, fewer words per minute, more pausing, more repetitions, more revisions, and more phonological fragments than controls, with only one exception: The Wernicke's group was similar to the control group in percentage of filled pauses. Individuals with Broca's aphasia had significantly longer inter-utterance pauses and fewer total words than all other aphasia groups. Both the Broca's and conduction aphasia groups had higher percentages of phrase repetitions than the NABW (NotAphasicByWAB) group. The conduction aphasia group also had a higher percentage of phrase revisions than the NABW and the anomic aphasia groups. Principal components analysis revealed two principal components that accounted for around 60% of the variance and related to quantity of output, rate of speech, and quality of output. The Gaussian mixture models showed that the participants clustered in three groups, which corresponded predominantly to the controls, the nonfluent aphasia group, and the remaining aphasia groups (all classically fluent aphasia types). CONCLUSIONS: FLUCALC is an efficient way to measure objective fluency behaviors in language samples in aphasia. Automated analyses of objective fluency behaviors on large samples of adults with and without aphasia can produce measures that can be used by researchers and clinicians to better understand and track salient aspects of fluency in aphasia. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25979863.

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).