Language Sample Analysis Research Articles

Factors affecting speech-language pathologists’ language assessment procedures and tools – challenges and future directions in Sweden

Purpose: National surveys of speech-language pathologists’ (SLP) practices play an important role in professional development, and previous research show that many challenges faced by the profession are similar across the globe. This study aims to describe Swedish SLP assessment practices, examine factors that may affect this practice, and discuss the results in the light of international studies. Methods: Data from 584 SLPs were collected through an online questionnaire with multiple choice and open-ended questions. A mixed-method design was deployed where a deductive qualitative analysis of free-text responses complemented quantitative data. Results: In line with previous results from English-speaking countries, both standardized discrete skill tests and contextualized assessments were used by the respondents but fewer used language sample analysis and dynamic assessment procedures, despite international recommendations. There were few differences based on experience, work setting, proportion of multilingual assessments and socio-economic status of the health catchment area. Main challenges reported were lack of time and difficulty prioritizing, and assessment and/or diagnosis of multilingual/L2 children, which is similar to challenges faced by SLPs in other countries. Swedish SLPs also reported lack of national clinical guidelines as a main challenge. Factors contributing to better assessments included experience, and the combination of many sources of information, including professional and interprofessional discussions. Conclusions: The accumulated evidence from this and previous studies show that to address challenges and build on strengths, changes on a systemic level are needed. This includes more time and resources for continuing education and implementation of recommended assessment methods, as well as professional and interprofessional collaborations.

A Sweet Tutorial to the SUGAR Method of Language Sampling

Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins with an overview of current LSA use, including barriers to clinical implementation, followed by an overview of the SUGAR method. Next, the SUGAR method is described in detail, including collecting the sample, transcribing the sample, analyzing the sample, and interpreting the results. To illustrate the method, each section includes an accompanying appendix that provides an example of a sample transcript and the various analyses. Conclusions: SUGAR offers speech-language pathologists one way to conduct LSA that is cost free, valid, and efficient. Clinicians can collect, transcribe, and analyze samples in approximately 21 min. The results of a SUGAR analysis can be used to document the presence of a language impairment, obtain a detailed description of a child's conversational language use, identify intervention targets, and develop intervention goals.

Disentangling the Grammar of 3- to 6-Year-Old Dutch Children With a Developmental Language Disorder.

Children with a developmental language disorder (DLD) are often delayed in their grammatical development. This is suggested to be the most important characteristic and clinical marker of DLD. However, it is unknown if this assumption is valid for young children, in the earliest stages of grammatical development. For this reason, this study investigates the complexity, diversity, and accuracy of the grammatical repertoires of 3- to 6-year-old Dutch children with DLD, in comparison to that of typically developing (TD) children matched on grammatical level. Language samples of 59 children (29 children with DLD and 30 TD children) were analyzed using multiple measures of grammatical complexity, diversity, and accuracy. The TD children and children with DLD were language-matched on their grammatical development using the levels of the Dutch version of the Language Assessment, Remediation, and Screening Procedure, the Taal Analyse Remediëring en Screening Procedure (TARSP; Schlichting, 2017). Thus, the children with DLD were significantly older than the TD children (respectively DLD age range: 2;7-5;4 [years;months], M age = 4;1; and TD age range: 2;0-3;9, M age = 2;9). The results show that children with DLD are comparable to language-matched TD children in their grammatical accuracy and diversity, but that they produce less complex utterances. The results indicate that children with DLD lag behind in their grammatical complexity as compared to language-matched TD children. The results also suggest that grammatical TARSP level is not sufficiently informative for selecting treatment goals. Instead, the results underline the importance of conducting language sample analyses, with special reference to the complexity of the utterances of a child with DLD.

The emergence of subjects in Lebanese two-year-olds.

In Lebanese Arabic, lexical subjects may occur before or after verbs, but only before non-verbal predicates. Analysis of spontaneous language samples from 19 two-year-old children shows that postverbal (VS) and preverbal (SV) subjects emerge simultaneously. The youngest children displayed no VS-SV difference in frequency. A slight preference for SV is observed in older children. No preference for SV subjects was found in the speech of the mothers of the younger or older children. Lexical subjects systematically appeared before non-verbal predicates. We interpret these results as evidence for early knowledge of syntactic movement, consistent with Wexler's (1998) Very Early Parameter Setting.

Sharpening Our Tools: A Systematic Review to Identify Diagnostically Accurate Language Sample Measures.

This systematic review provides a comprehensive summary of the diagnostic accuracy of English language sample analysis (LSA) measures for the identification of developmental language disorder. An electronic database search was conducted to identify English publications reporting empirical data on the diagnostic accuracy of English LSA measures for children aged 3 years or older. Twenty-eight studies were reviewed. Studies included between 18 and 676 participants ranging in age from 3;0 to 13;6 (years;months). Analyzed measures targeted multiple linguistic domains, and diagnostic accuracy ranged from less than 25% to greater than 90%. Morphosyntax measures achieved the highest accuracy, especially in combination with length measures, and at least one acceptable measure was identified for each 1-year age band up to 10 years old. Several LSA measures or combinations of measures are clinically useful for the identification of developmental language disorder, although more research is needed to replicate findings using rigorous methods and to explore measures that are informative for adolescents and across diverse varieties of English. https://doi.org/10.23641/asha.21183247.

Code-Switching by Spanish–English Bilingual Children in a Code-Switching Conversation Sample: Roles of Language Proficiency, Interlocutor Behavior, and Parent-Reported Code-Switching Experience

Code-switching is a complex bilingual behavior that can be affected by a variety of factors related to characteristics of the speaker, the interlocutor, and the broader sociolinguistic context. A better understanding of these factors is important for interpreting children’s use of code-switching in different elicitation contexts across research studies and in applied settings, such as language sample analysis for clinical assessment. In the current study, we used a conversation sample protocol with a code-switching adult interlocutor to examine the use of English, Spanish, intra-sentential and inter-sentential code-switching, and alignment with the interlocutor by Spanish/English bilingual children with a wide range of language abilities. In a single-language comparison condition, the same examiner engaged the child in conversation using only English or only Spanish. Key findings include that children exhibited limited use of code-switching in the English condition and similar frequency of code-switching in the Spanish, compared to the code-switching, conditions. Children exhibited a tendency to align with the examiner in their use of English vs. Spanish and their use of intra-sentential code-switching during the code-switching context, although they generally code-switched less than the examiner. There was also considerable variability across children. Predictors of this variability included children’s age and language proficiency. However, language proficiency was not associated with the frequency of children’s intra-sentential code-switching in a code-switching context. Parent-report measures of code-switching experience exhibited limited associations with the children’s observed code-switching behavior; inter-sentential switches into English showed the most direct associations. Based on the findings from this exploratory study, we highlight the importance of including a code-switching context when analyzing language samples from bilingual children, considering both the target child and the interlocutor’s behavior, and continuing to refine indirect report measures of code-switching experience.

Comparing Measures From Computer-Administered and Examiner-Administered Narrative Retells in Spanish: A Pilot Study.

Narrative language sample analysis (LSA) is a recommended best practice for the assessment of monolingual and bilingual children. With business-as-usual narrative LSA, examiners are actively involved in all aspects of the elicitation. Software advancements have shown multiple benefits of computer-administered language assessments, some of which may be beneficial for narrative assessments, particularly for bilingual children. The goal of this pilot study was to test the feasibility of computer-administered narrative retells in bilingual children. Ten English-Spanish bilingual children, kindergarten to fourth grade, completed two narrative retells using wordless picture books (Frog Goes to Dinner and Frog on His Own) in two conditions: examiner-administered and computer-administered. Five narrative measures were generated from these 20 transcripts. Significant, strong correlations were observed between the two elicitation methods for four of the five measures. We completed a series of Wilcoxon signed-ranks tests and found no significant differences in measures across the elicitation methods. Follow-up descriptive analyses revealed few large differences across elicitation methods for the individual participants. This study provides preliminary evidence on the use of a computer-administered narrative procedure and motivates further research on the method to confirm its validity and to document its effectiveness within clinical practice. https://doi.org/10.23641/asha.20346648.

Automated Progress-Monitoring for Literate Language Use in Narrative Assessment (LLUNA).

Language sample analysis (LSA) is an important practice for providing a culturally sensitive and accurate assessment of a child's language abilities. A child's usage of literate language devices in narrative samples has been shown to be a critical target for evaluation. While automated scoring systems have begun to appear in the field, no such system exists for conducting progress-monitoring on literate language usage within narratives. The current study aimed to develop a hard-coded scoring system called the Literate Language Use in Narrative Assessment (LLUNA), to automatically evaluate six aspects of literate language in non-coded narrative transcripts. LLUNA was designed to individually score six literate language elements (e.g., coordinating and subordinating conjunctions, meta-linguistic and meta-cognitive verbs, adverbs, and elaborated noun phrases). The interrater reliability of LLUNA with an expert scorer, as well as its' reliability compared to certified undergraduate scorers was calculated using a quadratic weighted kappa (Kqw). Results indicated that LLUNA met strong levels of interrater reliability with an expert scorer on all six elements. LLUNA also surpassed the reliability levels of certified, but non-expert scorers on four of the six elements and came close to matching reliability levels on the remaining two. LLUNA shows promise as means for automating the scoring of literate language in LSA and narrative samples for the purpose of assessment and progress-monitoring.

Language sample analysis consideration and use: a survey of school-based speech language pathologists

Purpose: The purpose of the current study was to extend previous knowledge on the language sample analysis (LSA) practices of school-based speech-language pathologists (SLPs) by gathering information on the processes, procedures, clinical judgments, and decisions that current school-based SLPs make during the context of conducting an LSA.Methods: School-based SLPs responded to a survey on current practices, perceived knowledge, knowledge of current recommended practices, and education and training in LSA.Results: Results indicated the majority of school-based SLPs used LSA (90%) during evaluations to supplement information provided on norm-referenced tests and as a naturalistic language measure. However, the results also demonstrate a lack of knowledge of current recommended practices. The respondents, on average, only answered 50% of the knowledge questions correctly.Conclusions: Participant responses to knowledge and practice questions indicated a continued gap in current LSA practice including the context of collected samples, the transcription and recording process, and the analysis measures completed. Additionally, the results indicated a need to look closely at the undergraduate and graduate curriculum on LSA as the respondents indicated the largest amount of education and training coming from these programs.

Language Sample Analysis With TalkBank: An Update and Review

This chapter examines state-of-the-art methods for coding, analyzing, and interpreting discourse-level language data from children and adults with language disorders using the data, tools, and methods provided by the TalkBank system (https://www.talkbank.org). These open and free methods have been used for language sample analysis (LSA) with several clinical populations (e.g., child language disorders, stuttering, aphasia, dementia, traumatic brain injury, right hemisphere brain damage), as well as with control participants without communication impairments. We review the six core principles guiding TalkBank, the current shape of the 15 TalkBank databanks, and the different analytic tools provided by TalkBank. We examine automatic TalkBank methods that use ASR (automatic speech recognition), NLP (natural language processing), database technology, statistics in R and Python, and ML (machine learning). The specific tools include corpus analysis methods, LSA profiling systems, online database searches through TalkBank, online browsing through transcripts linked to media, and a new system for online collaborative commentary. These systems provide multimedia access to transcripts from a wide variety of participants with and without language disorders.

The Reliability of Short Conversational Language Sample Measures in Children With and Without Developmental Language Disorder.

Language sample analysis (LSA) represents an ecologically valid method for diagnosing, identifying goals, and measuring progress in children with developmental language disorder (DLD). LSA is, however, time consuming. The purpose of this study was to determine the length of sample needed to obtain reliable LSA measures for children in kindergarten and first grade with typical language (TL) and DLD using automated analyses from the Systematic Analysis of Language Transcripts software. Play-based conversational language samples collected on kindergarten to first-grade children with TL (n = 21) and DLD (n = 21) from a community-based sample were analyzed. Eight LSA measures were calculated from 1-, 3-, 5-, 7-, and 10-min sample cuts and compared to 20-min samples for reliability. Reliability estimates were similar for the TL and DLD groups except for errors and omissions, which showed overall higher levels of reliability in the DLD group and reached acceptable levels at 3 min. Percent grammatical utterances were reliable at 7 min in the DLD group and not reliable in shorter samples in the TL group. The subordination index was reliable at 10 min for both groups. Number of different words reached acceptable reliability at the 3-min length for the DLD group and at the 10-min length for the TL group. Utterances and words per minute were reliable at 3 min and mean length of utterance at 7 min in both groups. Speech-language pathologists can obtain reliable LSA measures from shorter, 7-min conversational language samples from kindergarten to first-grade children with DLD. Shorter language samples may encourage increased use of LSA. https://doi.org/10.23641/asha.19529287.

Preschool Minority Children's Persian Vocabulary Development: A Language Sample Analysis.

This study linked background TV and socioeconomic status (SES) to minority children’s Persian vocabulary development. To this end, 80 Iranian preschool children (aged 5–6 years old) from two minority groups of Arabs and Turks were selected using stratified random sampling. They were simultaneous bilinguals, i.e., their mother tongue was either Arabic or Azari and their first language was Persian. Language sample analysis (LSA) was used to measure vocabulary development through a 15-min interview by language experts (PhD in applied linguistics). The LSA measures included total number of utterances (TNU), total number of words (TNW), total number of new words (NDW), and mean length of utterance (MLU). A series of independent-samples t test, paired-samples t test, and repeated measures MANOVA tests were ran to examine data. Results showed significant improvements in children’s vocabulary scores from pretest to posttest for all children. In addition, high-SES children scored higher on the vocabulary measures in pretest and posttest. Moreover, background TV was associated with higher means in the TNW and the NDW in groups. The researchers concluded that background TV may be related to higher vocabulary scores in low-SES families as it may compensate for some linguistics gaps in these families including lower amount of child-parent interaction, play, and parents’ level of literacy.

Predicting Language Performance From Narrative Language Samples.

Analysis of narrative language samples is a recommended clinical practice in the assessment of children's language skills, but we know little about how results from such analyses relate to overall oral language ability across the early school years. We examined the relations between language sample metrics from a short narrative retell, collected in kindergarten, and an oral language factor in grades kindergarten through 3. Our specific questions were to determine the extent to which metrics from narrative language sample analysis are concurrently related to language in kindergarten and predict language through Grade 3. Participants were a sample of 284 children who were administered a narrative retell task in kindergarten and a battery of vocabulary and grammar measures in kindergarten through Grade 3. Language samples were analyzed for number of different words, mean length of utterance, and a relatively new metric, percent grammatical utterances (PGUs). Structural equation models were used to estimate the concurrent and longitudinal relationships. The narrative language sample metrics were consistently correlated with the individual vocabulary and grammar measures as well as the language factor in each grade, and also consistently and uniquely predicted the language factor in each grade. Standardized path estimates in the structural equation models ranged from 0.20 to 0.39. This study found narrative language sample metrics to be predictive, concurrently and longitudinally, of a latent factor of language from kindergarten through Grade 3. These results further validate the importance of collecting and analyzing narrative language samples, to include PGU along with more traditional metrics, and point to directions for future research. https://doi.org/10.23641/asha.17700980.

Autistic preschoolers' engagement and language use in gross motor versus symbolic play settings.

Background and aims: Although adjustment of the environment is recommended as a support strategy in evidence-based interventions for children with autism, the impact of doing so (and the how and why) is not well understood. One essential environmental factor to consider when providing supports for preschool-aged autistic children is the play setting, specifically, the materials available in the child's play context. The aim of this study was to compare engagement states and number of utterances produced by preschool-aged autistic children within symbolic vs. gross motor play settings. Examining the relationship between gross motor play settings and children's social engagement and spoken language use is particularly important to explore for autistic children given differences in their sensory processing, motor skill development, and choice of and interaction with toys relative to neurotypical peers. Methods: Seventy autistic children aged 25-57 months were videotaped during natural play interactions with a parent. Children's social engagement and number of spoken utterances were examined in five minutes each of play with symbolic toys and play with gross motor toys. Continuous time-tagged video coding of the child-caregiver engagement states was conducted, and the child's frequency of spoken language was identified using language sample analysis. The specific variables examined were; (a) engagement with caregiver, (b) engagement with objects only, (c) unengaged (no evident engagement with objects or people), and (d) total number of spoken utterances. The relationship between play setting (symbolic vs gross motor) and child language and engagement state variables was examined with linear mixed effects modelling. Results: Significant main effects were revealed for the interaction between play setting and autistic children's engagement. Young autistic children were more likely to engage with caregivers in play environments with gross motor toys (moderate effect) and also were more likely to have periods of unengaged time (not overtly directing their attention to objects or people; small effect) in this setting. Further, when in a setting with symbolic toys, autistic children were more likely to spend their time focusing attention solely on objects (large effect). No interaction was found between play setting and total number of utterances spoken by autistic children. Conclusions and implications: This study confirmed the importance of continued research focused on understanding the relationship between children's play settings and their social engagement and language use. Although preliminary, findings support the idea that there is an interaction between preschool-aged autistic children's social engagement and their play settings. Further, our results suggest that there can be value in clinicians differentiating children's play settings (i.e., gross motor vs symbolic) when assessing and supporting social engagement capacities of young autistic children.

ЛИЧНОСТЬ ДРУГОГО В АКАДЕМИЧЕСКОМ ДИСКУРСЕ

The paper focuses on the semantic role of Other in academic discourse. Drawing on ideas expressed by M.M. Bakhtin and Yu.M. Lotman, the authors see Other as a key actor of written communication in the academic community and aim to describe the specifics of verbalizing Other’s presence in academic discourse as compared to fiction genres. The empirical basis of the study is constituted by a corpus of research papers written by Russian linguists and published over the period of 1991 through 2012 as part of the Logical Analysis of Language series edited by N.D. Arutyunova. In the initial stage of the research the corpus was used as a source of language data featuring contexts indicative of omnipresent Other. The second stage consisted in semantic analysis of language samples followed by cognitive interpretation and relied both on present-day linguistic theories and recent research in psychology. Results include a typology of Other in academic discourse and a description of relevant lexical and syntactic units systemically functioning as explicit and implicit markers of Other in Russian written academic communication. Addressing the figure of Other in academic discourse offers insights on the cognitive background of academic communication and brings to light key pragmatic intentions shaping interaction within the academic community

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

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. 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. 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. 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. https://doi.org/10.23641/asha.16915690.

Language Sample Analysis in Clinical Practice: Speech-Language Pathologists' Barriers, Facilitators, and Needs.

Most speech-language pathologists (SLPs) working with children with developmental language disorder (DLD) do not perform language sample analysis (LSA) on a regular basis, although they do regard LSA as highly informative for goal setting and evaluating grammatical therapy. The primary aim of this study was to identify facilitators, barriers, and needs related to performing LSA by Dutch SLPs working with children with DLD. The secondary aim was to investigate whether a training would change the actual performance of LSA. A focus group with 11 SLPs working in Dutch speech-language pathology practices was conducted. Barriers, facilitators, and needs were identified using thematic analysis and categorized using the theoretical domain framework. To address the barriers, a training was developed using software program CLAN. Changes in barriers and use of LSA were evaluated with a survey sent to participants before, directly after, and 3 months posttraining. The barriers reported in the focus group were SLPs' lack of knowledge and skills, time investment, negative beliefs about their capabilities, differences in beliefs about their professional role, and no reimbursement from health insurance companies. Posttraining survey results revealed that LSA was not performed more often in daily practice. Using CLAN was not the solution according to participating SLPs. Time investment remained a huge barrier. A training in performing LSA did not resolve the time investment barrier experienced by SLPs. User-friendly software, developed in codesign with SLPs might provide a solution. For the short-term, shorter samples, preferably from narrative tasks, should be considered.

Systematic Analysis of Language Transcripts’ (SALT) transcribing method and Narrative Assessment Protocol (NAP) online coding method: are they interchangeable?

Purpose: A narrative is a reliable tool for assessing the child’s oral language. There are various narrative assessment tools. Most of them follow the Language Sample Analysis method such as Systematic Analysis of Language Transcripts (SALT) which is time-consuming and needs extensive training. The Narrative Assessment Protocol (NAP) offers a free and faster method of assessment to administer. The current study compared the NAP online and offline coding methods. Methods: Fifty-two kindergarteners (40–66 months old) were voice-recorded while generating a story. A transcriber coded the samples using both online and offline methods. Then, relative and absolute reliabilities were measured. Results: The results indicate a high correlation between the NAP offline and online scoring methods. Aside from a few items, both methods showed good correlations with each other. Conclusions: The NAP online coding method can be used as an alternative to an offline transcription to obtain a quick picture of a child's microstructure measures in narration.

Assessment of minority language skills in English-Irish-speaking bilingual children: A survey of SLT perspectives and current practices.

An increasing number of children in the UK and Ireland are growing up speaking more than one language. The many advantages of bilingualism are acknowledged; however, this increased linguistic diversity presents particular challenges for speech and language therapists (SLTs). The case is often more complex with speakers of minority languages such as Welsh and Irish, which are acquired almost exclusively in bilingual contexts. Lack of appropriate standardized assessments for bilinguals is a key issue for SLTs internationally; however, little is known about the practices, personal perspectives or wider challenges faced by SLTs in assessing minority language skills. We focus on SLTs working with English-Irish bilinguals across Northern Ireland (NI) and the Republic of Ireland (ROI) where status, use and exposure to Irish differ significantly. To investigate the perceptions and practices of SLTs in NI and the ROI in the assessment of bilingual English-Irish-speaking children. A 33-item online survey was distributed to SLTs working with children in community settings in NI and the ROI. A total of 181 SLTs completed the survey. The majority of respondents had bilingual English-Irish-speaking children on their caseloads; however, less than one-quarter had assessed Irish language skills. Responses indicate confusion as to whether best-practice guidelines applied in this particular context where the majority of speakers have English as their first language and limited domains of exposure to Irish outside of the education system. Resources available to assess Irish language skills were found to be limited. Informal analysis of language samples emerged as the most popular assessment tool. SLTs in the ROI had a significantly higher level of competence in the Irish language than SLTs in NI. This reduced the challenge of assessment. Many SLTs reported scoring assessments standardized on monolingual populations when assessing English language skills in bilingual English-Irish-speaking children. Our findings highlight the challenges faced by SLTs in meeting best-practice guidelines in the assessment of speakers of minority languages such as Irish. Further work is needed to ensure clinicians and other professionals have access to information and enhanced training on bilingual language acquisition in minority language contexts and implications for assessment and diagnosis. This study underlines the need for further research on the acquisition of minority languages as well as the development of alternative assessment tools to assist SLTs in meeting the needs of this population. What is already known on the subject Existing research indicates that SLTs face challenges in assessing bilingual clients. Lack of assessment resources is a global issue, particularly with respect to minority languages. Emerging research indicates that SLTs and other professionals are dissatisfied with current resources for assessing Irish-speaking bilinguals and are struggling to meet best-practice guidelines. What this paper adds to existing knowledge The status of the Irish language differs significantly between NI and the ROI, while English is the dominant language in both areas. This study provides the first exploration of current assessment practices for bilingual English-Irish-speaking children as reported by SLTs across both regions. The challenges of assessing bilingual clients in many other countries are mirrored by SLTs in NI and the ROI. The majority of children acquiring Irish are doing so in a specific context: the immersion education setting. This raises uncertainty for SLTs about whether the definition of bilingualism actually applies. Despite clinicians and clients sharing the same majority language, the complexity of minority language assessment remains. What are the potential or actual clinical implications of this work? SLTs require specific support and resources to help them meet the assessment needs of bilingual English-Irish-speaking children. Ongoing education and training are required for clinicians and other professionals to facilitate understanding of the complexities surrounding bilingual speakers of minority languages and the application of best-practice guidelines. A greater understanding of the context in which children are acquiring Irish and the impact this may have on their acquisition of English would further support clinicians in identifying speech, language and communication needs in this population.

An Evaluation of Expedited Transcription Methods for School-Age Children's Narrative Language: Automatic Speech Recognition and Real-Time Transcription.

Purpose This study examined the accuracy and potential clinical utility of two expedited transcription methods for narrative language samples elicited from school-age children (7;5-11;10 [years;months]) with developmental language disorder. Transcription methods included real-time transcription produced by speech-language pathologists (SLPs) and trained transcribers (TTs) as well as Google Cloud Speech automatic speech recognition. Method The accuracy of each transcription method was evaluated against a gold-standard reference corpus. Clinical utility was examined by determining the reliability of scores calculated from the transcripts produced by each method on several language sample analysis (LSA) measures. Participants included seven certified SLPs and seven TTs. Each participant was asked to produce a set of six transcripts in real time, out of a total 42 language samples. The same 42 samples were transcribed using Google Cloud Speech. Transcription accuracy was evaluated through word error rate. Reliability of LSA scores was determined using correlation analysis. Results Results indicated that Google Cloud Speech was significantly more accurate than real-time transcription in transcribing narrative samples and was not impacted by speech rate of the narrator. In contrast, SLP and TT transcription accuracy decreased as a function of increasing speech rate. LSA metrics generated from Google Cloud Speech transcripts were also more reliably calculated. Conclusions Automatic speech recognition showed greater accuracy and clinical utility as an expedited transcription method than real-time transcription. Though there is room for improvement in the accuracy of speech recognition for the purpose of clinical transcription, it produced highly reliable scores on several commonly used LSA metrics. Supplemental Material https://doi.org/10.23641/asha.15167355.