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.

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.

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.

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.

An open dataset of connected speech in aphasia with consensus ratings of auditory-perceptual features.

Purpose: Auditory-perceptual rating of connected speech in aphasia (APROCSA) involves trained listeners rating a large number of perceptual features of speech samples, and has shown promise as an approach for quantifying expressive speech and language function in individuals with aphasia. The aim of this study was to obtain consensus ratings for a diverse set of speech samples, which can then be used as training materials for learning the APROCSA system. Method: Connected speech samples were recorded from six individuals with chronic post-stroke aphasia. A segment containing the first five minutes of participant speech was excerpted from each sample, and 27 features were rated on a five-point scale by five researchers. The researchers then discussed each feature in turn to obtain consensus ratings. Results: Six connected speech samples are made freely available for research, education, and clinical uses. Consensus ratings are reported for each of the 27 features, for each speech sample. Discrepancies between raters were resolved through discussion, yielding consensus ratings that can be expected to be more accurate than mean ratings. Conclusions: The dataset will provide a useful resource for scientists, students, and clinicians to learn how to evaluate aphasic speech samples with an auditory-perceptual approach.

Making Sense of Right Hemisphere Discourse Using RHDBank.

PURPOSE: Right hemisphere brain damage (RHD) commonly causes pragmatic language disorders that are apparent in discourse production. Specific characteristics and approaches to assessment, diagnosis, and treatment of these disorders are not well-defined. RHDBank, a shared database of multimedia interactions for the study of communication using discourse, was created to address these gaps. The database, materials, and related analysis programs are free resources to clinicians, researchers, educators, and students. METHOD: A standard discourse protocol was developed to elicit multiple types of discourse: free speech, conversation, picture description, storytelling, procedural discourse, and question-asking. Testing included measures of cognition, unilateral neglect, and communicative participation. Language samples were video-recorded and transcribed in CHAT format. Currently, the database includes 24 adults with RHD and 24 controls. RESULTS: Illustrative analyses show how RHDBank can facilitate research using micro- and macrolinguistic discourse analysis techniques both within this population and across populations. Educational resources, such as the Grand Rounds tutorial, were developed using case studies from the database. CONCLUSIONS: RHDBank is a shared database of resources that can facilitate educational and research efforts to address the gaps in knowledge about RHD communication and improve the clinical management of individuals with RHD.

Spoken Discourse Assessment and Analysis in Aphasia: An International Survey of Current Practices.

Purpose Spoken discourse analysis is commonly employed in the assessment and treatment of people living with aphasia, yet there is no standardization in assessment, analysis, or reporting procedures, thereby precluding comparison/meta-analyses of data and hindering replication of findings. An important first step is to identify current practices in collecting and analyzing spoken discourse in aphasia. Thus, this study surveyed current practices, with the goal of working toward standardizing spoken discourse assessment first in research settings with subsequent implementation into clinical settings. Method A mixed-methods (quantitative and qualitative) survey was publicized to researchers and clinicians around the globe who have collected and/or analyzed spoken discourse data in aphasia. The survey data were collected between September and November 2019. Results Of the 201 individuals who consented to participate, 189 completed all mandatory questions in the survey (with fewer completing nonmandatory response questions). The majority of respondents reported barriers to utilizing discourse including transcription, coding, and analysis. The most common barrier was time (e.g., lack of time). Respondents also indicated that there was a lack of, and a need for, psychometric properties and normative data for spoken discourse use in the assessment and treatment of persons with aphasia. Quantitative and qualitative results are described in detail. Conclusions The current survey study evaluated spoken discourse methods in aphasia across research and clinical settings. Findings from this study will be used to guide development of process standardization in spoken discourse and for the creation of a psychometric and normative property database. Supplemental Material https://doi.org/10.23641/asha.166395100.

A Comparison of Manual Versus Automated Quantitative Production Analysis of Connected Speech.

Purpose Analysis of connected speech in the field of adult neurogenic communication disorders is essential for research and clinical purposes, yet time and expertise are often cited as limiting factors. The purpose of this project was to create and evaluate an automated program to score and compute the measures from the Quantitative Production Analysis (QPA), an objective and systematic approach for measuring morphological and structural features of connected speech. Method The QPA was used to analyze transcripts of Cinderella stories from 109 individuals with acute-subacute left hemisphere stroke. Regression slopes and residuals were used to compare the results of manual scoring and automated scoring using the newly developed C-QPA command in CLAN, a set of programs for automatic analysis of language samples. Results The C-QPA command produced two spreadsheet outputs: an analysis spreadsheet with scores for each utterance in the language sample, and a summary spreadsheet with 18 score totals from the analysis spreadsheet and an additional 15 measures derived from those totals. Linear regression analysis revealed that 32 of the 33 measures had good agreement; auxiliary complexity index was the one score that did not have good agreement. Conclusions The C-QPA command can be used to perform automated analyses of language transcripts, saving time and training and providing reliable and valid quantification of connected speech. Transcribing in CHAT, the CLAN editor, also streamlined the process of transcript preparation for QPA and allowed for precise linking of media files to language transcripts for temporal analyses.

Standardizing Assessment of Spoken Discourse in Aphasia: A Working Group With Deliverables.

Purpose The heterogeneous nature of measures, methods, and analyses reported in the aphasia spoken discourse literature precludes comparison of outcomes across studies (e.g., meta-analyses) and inhibits replication. Furthermore, funding and time constraints significantly hinder collecting test-retest data on spoken discourse outcomes. This research note describes the development and structure of a working group, designed to address major gaps in the spoken discourse aphasia literature, including a lack of standardization in methodology, analysis, and reporting, as well as nominal data regarding the psychometric properties of spoken discourse outcomes. Method The initial initiatives for this working group are to (a) propose recommendations regarding standardization of spoken discourse collection, analysis, and reporting in aphasia, based on the results of an international survey and a systematic literature review and (b) create a database of test-retest spoken discourse data from individuals with and without aphasia. The survey of spoken discourse collection, analysis, and interpretation procedures was distributed to clinicians and researchers involved in aphasia assessment and rehabilitation from September to November 2019. We will publish survey results and recommend standards for collecting, analyzing, and reporting spoken discourse in aphasia. A multisite endeavor to collect test-retest spoken discourse data from individuals with and without aphasia will be initiated. This test-retest information will be contributed to a central site for transcription and analysis, and data will be subsequently openly curated. Conclusion The goal of the working group is to create recommendations for field-wide standards in methods, analysis, and reporting of spoken discourse outcomes, as has been done across other related disciplines (e.g., Consolidated Standards of Reporting Trials, Enhancing the Quality and Transparency of Health Research, Committee on Best Practice in Data Analysis and Sharing). Additionally, the creation of a database through our multisite collaboration will allow the identification of psychometrically sound outcome measures and norms that can be used by clinicians and researchers to assess spoken discourse abilities in aphasia.

Automation of the Northwestern Narrative Language Analysis System.

Purpose Analysis of spontaneous speech samples is important for determining patterns of language production in people with aphasia. To accomplish this, researchers and clinicians can use either hand coding or computer-automated methods. In a comparison of the two methods using the hand-coding NNLA (Northwestern Narrative Language Analysis) and automatic transcript analysis by CLAN (Computerized Language Analysis), Hsu and Thompson (2018) found good agreement for 32 of 51 linguistic variables. The comparison showed little difference between the two methods for coding most general (i.e., utterance length, rate of speech production), lexical, and morphological measures. However, the NNLA system coded grammatical measures (i.e., sentence and verb argument structure) that CLAN did not. Because of the importance of quantifying these aspects of language, the current study sought to implement a new, single, composite CLAN command for the full set of 51 NNLA codes and to evaluate its reliability for coding aphasic language samples. Method Eighteen manually coded NNLA transcripts from eight people with aphasia and 10 controls were converted into CHAT (Codes for the Human Analysis of Talk) files for compatibility with CLAN commands. Rules from the NNLA manual were translated into programmed rules for CLAN computation of lexical, morphological, utterance-level, sentence-level, and verb argument structure measures. Results The new C-NNLA (CLAN command to compute the full set of NNLA measures) program automatically computes 50 of the 51 NNLA measures and generates the results in a summary spreadsheet. The only measure it does not compute is the number of verb particles. Statistical tests revealed no significant difference between C-NNLA results and those generated by manual coding for 44 of the 50 measures. C-NNLA results were not comparable to manual coding for the six verb argument measures. Conclusion Clinicians and researchers can use the automatic C-NNLA to analyze important variables required for quantification of grammatical deficits in aphasia in a way that is fast, replicable, and accessible without extensive linguistic knowledge and training.

Question Use in Adults With Right-Hemisphere Brain Damage.

Purpose Right-hemisphere brain damage (RHD) can affect pragmatic aspects of communication that may contribute to an impaired ability to gather information. Questions are an explicit means of gathering information. Question types vary in terms of the demands they place on cognitive resources. The purpose of this exploratory descriptive study is to test the hypothesis that adults with RHD differ from neurologically healthy adults in the types of questions asked during a structured task. Method Adults who sustained a single right-hemisphere stroke and neurologically healthy controls from the RHDBank Database completed the Unfamiliar Object Task of the RHDBank Discourse Protocol (Minga et al., 2016). Each task was video-recorded. Questions were transcribed using the Codes for the Human Analysis of Transcripts format. Coding and analysis of each response were conducted using Computerized Language Analysis (MacWhinney, 2000) programs. Results The types of questions used differed significantly across groups, with the RHD group using significantly more content questions and significantly fewer polar questions than the neurologically healthy control group. In their content question use, adults with RHD used significantly more "what" questions than other question subtypes. Conclusion Question-asking is an important aspect of pragmatic communication. Differences in the relative usage of question types, such as the reduced use of polar questions or increased use of content questions, may reflect cognitive limitations arising from RHD. Further investigations examining question use in this population are encouraged to replicate the current findings and to expand on the study tasks and measures. Supplemental Material https://doi.org/10.23641/asha.11936295.

Using AphasiaBank for Discourse Assessment.

AphasiaBank is a shared, multimedia database for the study of communication in aphasia. This article describes a variety of discourse measurement tools and teaching resources available at the AphasiaBank website. The discourse measurement tools include main concept analysis, core lexicon checklists, correct information unit computation techniques, and other automated analyses using the CLAN program. These tools can be used to measure a variety of aspects of language production for assessment as well as treatment evaluation and clinical research purposes. Importantly, they are intended to help make the discourse analysis process more efficient and reliable. Teaching resources include an online tutorial on aphasia, videos of typical behaviors seen in aphasia, group treatment videos, classroom activities, tutorial screencasts, and conference posters. These resources can be used for a variety of clinical and educational purposes. The AphasiaBank website is part of the larger TalkBank project which provides many other shared databases and resources that are relevant to professionals interested in communication and communication disorders.

Patterns of narrative discourse in early recovery following severe Traumatic Brain Injury.

Primary Objective: To investigate the nature and patterns of narrative discourse impairment in people with severe Traumatic Brain Injury (TBI) during early recovery.Methods and Procedures: A single image picture description task was administered to 42 participants with severe TBI at 3 and 6-months post-injury. The same task was administered to 37 control participants. Discourse samples were analyzed with measures of productivity, informativeness and story organization. The performance of people with TBI was compared with the control group at both 3 and 6 months, and the performance of the participants with TBI was also compared across the two time points. Individual patterns of performance were also examined.Results: Inferential analyses revealed significant differences between the control group and the group with TBI on informativeness at both time points and  number of complete episodes at 3 months, but no significant differences for productivity measures. There was no significant change for the group with TBI between 3 and 6 months. However, individual improvement over time was observed.Conclusions: People with TBI have discourse difficulties early post TBI that are also present at 6-months post-injury. In order to understand longer-term discourse recovery, it is necessary to examine participant patterns over further time points on this narrative task.