Predicting Language Performance From Narrative Language Samples

Purpose: 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. Method: 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. Results: 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. Conclusions: 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. Supplemental Material https://doi.org/10.23641/asha.17700980

Analysis of Connected Speech in Persian Aphasic Patients and its Relationship With Type and Severity of Aphasia

Background and Objectives: There are several tests to determine the type and severity of aphasia, but they take a long time to administer when assessing aphasic patients. In recent years, the analysis of spontaneous speech has gained great attention because it is important to diagnose and follow post-treatment improvement in aphasic patients. This study was done to assess some parameters of connected speech in aphasic patients. In addition, the correlation between connected speech parameters and the type and severity of aphasia was measured. Methods: We compared the connected speech parameters of 27 aphasics (10 fluent and 17 non-fluent), Persian speakers, compared with the control group. There were two groups matched by age, sex, and education. Nest’s bird story pictures were used to elicit a speech sample. In the next step, the connected speech was analyzed to define speech parameters, including speech rate, mean length of utterance, number of utterances, total words, content words, function words, nouns, and verbs. Moreover, the severity of aphasia was measured using a Persian Western Aphasia Battery (WAB). Results: The findings showed significant differences between groups in all parameters of the connected speech (P<0.01). The correlation coefficient between speech parameters and severity of aphasia demonstrated that all parameters were highly correlated (r >0.71) with the severity of aphasia (P<0.01) except for speech rate and the number of function words. There were some typical differences between linguistics grammatical and pragmatical characters of different types of aphasia. Conclusion: Connected speech is one of the most sensitive parts of language in all types of aphasic patients. There are some clinical signs for differential diagnosis of aphasia based on speech measures. According to the findings, the type and severity of aphasia and connected speech were highly correlated. Thus, the use of the connected speech analysis is necessary as an assessment tool for the diagnosis of aphasia.

Within- and Cross-Language Relations Between Phonological Memory, Vocabulary, and Grammar in Bilingual Children

Purpose This study investigated within-language and between-language associations between phonological memory, vocabulary, and grammar in French–English ( n = 43) and Spanish–English ( n = 25) bilingual children at 30, 36, and 48 months. It was predicted that phonological memory would display both within-language and between-language relations to language development and that these relations would be stronger at the youngest age. Method Bilingual children participated in free-play sessions in both of their languages at each age, from which vocabulary and grammatical information (number of different words and mean length of utterance) was extracted. Vocabulary information was also obtained from parent inventories completed when the children were 30 months and a standardized receptive vocabulary test administered at 36 and 48 months. The children were also administered nonword repetition tests in both of their languages at each age. Results Mixed logistic regression indicated that phonological memory was associated with vocabulary and grammar within the same language and phonological memory in the other language. In two of the four statistical models, phonological memory exhibited positive between-language relations, and in one model, it exhibited negative between-language relations to language development. Results also indicated that within-language and between-languages effects remained constant, or between-language associations decreased during the age range studied. Conclusion Overall, the findings provide some support for cross-language associations between phonological memory and lexical and grammatical skills.

Mean Length of Utterance of Children at the Trihita Alam Eco School

The aim of the study is mainly at testing the theory of Brown on the Mean Length of Utterance (MLU). Methods applied in this study were observation and audio recording technique. The data in this study were the utterances produced by students of Trihita Alam Eco School. There were sixteen children ranging from 4 to 6 years participating in this study (M=5.4). The children observed in this study are healthy children both physically and psychologically. The written permission from the school has been obtained to conduct the study. The results show that the sentence structures produced by children are quite well-organized and are able to place language functions clearly. The calculation of the MLU value in the research subjects show that Brown's theory which states that children at age 47 months have the MLU of 4.5 are mostly correct. The assumption that children who have the same ages doesn’t imply that they have the same MLU is proven right.

A Pseudo-Value Approach to Analyze the Semantic Similarity of the Speech of Children With and Without Autism Spectrum Disorder

Conversational impairments are well known among people with autism spectrum disorder (ASD), but their measurement requires time-consuming manual annotation of language samples. Natural language processing (NLP) has shown promise in identifying semantic difficulties when compared to clinician-annotated reference transcripts. Our goal was to develop a novel measure of lexico-semantic similarity – based on recent work in natural language processing (NLP) and recent applications of pseudo-value analysis – which could be applied to transcripts of children’s conversational language, without recourse to some ground-truth reference document. We hypothesized that: (a) semantic coherence, as measured by this method, would discriminate between children with and without ASD and (b) more variability would be found in the group with ASD. We used data from 70 4- to 8-year-old males with ASD (N = 38) or typically developing (TD; N = 32) enrolled in a language study. Participants were administered a battery of standardized diagnostic tests, including the Autism Diagnostic Observation Schedule (ADOS). ADOS was recorded and transcribed, and we analyzed children’s language output during the conversation/interview ADOS tasks. Transcripts were converted to vectors via a word2vec model trained on the Google News Corpus. Pairwise similarity across all subjects and a sample grand mean were calculated. Using a leave-one-out algorithm, a pseudo-value, detailed below, representing each subject’s contribution to the grand mean was generated. Means of pseudo-values were compared between the two groups. Analyses were co-varied for nonverbal IQ, mean length of utterance, and number of distinct word roots (NDR). Statistically significant differences were observed in means of pseudo-values between TD and ASD groups (p = 0.007). TD subjects had higher pseudo-value scores suggesting that similarity scores of TD subjects were more similar to the overall group mean. Variance of pseudo-values was greater in the ASD group. Nonverbal IQ, mean length of utterance, or NDR did not account for between group differences. The findings suggest that our pseudo-value-based method can be effectively used to identify specific semantic difficulties that characterize children with ASD without requiring a reference transcript.

PEMEROLEHAN BAHASA ANAK SUKU KARO SUMATERA UTARA (KAJIAN MEAN LENGTH OF UTTERANCE [MLU])

Bahasa dapat mengontrol perilaku, merealisasikan tindakan, dan mengubah situasi. Tujuan penelitian ini untuk meneliti pemerolehan bahasa anak daerah Suku Karo Usia 4 Tahun 9 Bulan Di Sumatera Utara (Kajian Mean Length Of Utterance [MLU]). Metode penelitian yang digunakan adalah metode deskriptif dengan analisis isi (content analysis). Hasil perhitungan mean length of utterance (MLU) Liliana yaitu 2,36 kata per tuturan disesuaikan dengan pendapat Brown berada pada tahap II MLU (2,25-2,5) pada usia 28-30 bulan. Berdasarkan hasil penelitian dan pembahasan diatas anak memiliki perkembangan bahasa yang tidak baik sehingga diperlukanya perubahan untuk meningkatkan perkembangan bahasa anak.

Tailoring the Input to Children's Needs: The Use of Fine Lexical Tuning in Speech Directed to Normally Hearing Children and Children With Cochlear Implants

Purpose: The aim of the present study was to explore fine lexical tuning in Dutch infant-directed speech (IDS) addressed to congenitally deaf infants who received a cochlear implant (CI) early in life (&lt;2 years of age) in comparison with children with normal hearing (NH). The longitudinal pattern of parents' utterance length in the initial stages of the child's lexical development was examined. Parents' utterances containing the words the children eventually acquired in the earliest developmental stages were selected and their MLU (Mean Length of Utterance) was measured.Method: Transcriptions of monthly recordings of spontaneous interactions of 10 CI children and 30 NH children with their parents were analyzed. The children with CI were followed from the moment their device was switched on, and the NH children from the age of 6 months onwards. A total of 57,846 utterances of parents of CI children and 149,468 utterances of parents of NH children were analyzed.Results: IDS addressed to children with NH and children with CI exhibits fine lexical tuning: parents adjust the MLU of the utterances that contain the words that children are on the verge of producing themselves. More specifically, the parents' mean length of those utterances decreased in relation to the point when the children began using the item. Consequently, the number of occurrences in isolation of the lexical item increased. The speech addressed to all the children exhibited this phenomenon, but it was significantly more strongly present in speech addressed to the children with CI.Conclusions: The speech addressed to children with NH and CI is characterized by fine lexical tuning and a high incidence of single-word utterances in the period leading up to the children's first use of words in speech production. Notwithstanding striking commonalities, IDS addressed to children with a hearing impairment is markedly different, which suggests that parents take this specific character of the children into account.

Individual differences in discourse priming

In this paper we use corpora of four monolingual German-speaking children at 2 years of age to analyze the effect of input on the activation of chunks and frame-and-slot patterns. For this purpose, we first investigate to what extent chunks and patterns can be traced back to the direct input compared to input which is not part of the immediate discourse situation. Second, we take mean length of utterance (MLU) into account to see how the level of proficiency influences the amount of priming in each child. Results indicate that children with a lower MLU rely more on priming than children who are more proficient. This conclusion is consistent with the usage-based assumption that children’s linguistic development starts with a strongly item-based reproduction of input patterns that gradually gives rise to increasingly creative and productive uses of constructions.

Evaluating atypical language in autism using automated language measures

Measurement of language atypicalities in Autism Spectrum Disorder (ASD) is cumbersome and costly. Better language outcome measures are needed. Using language transcripts, we generated Automated Language Measures (ALMs) and tested their validity. 169 participants (96 ASD, 28 TD, 45 ADHD) ages 7 to 17 were evaluated with the Autism Diagnostic Observation Schedule. Transcripts of one task were analyzed to generate seven ALMs: mean length of utterance in morphemes, number of different word roots (NDWR), um proportion, content maze proportion, unintelligible proportion, c-units per minute, and repetition proportion. With the exception of repetition proportion (p $$= .07$$ = . 07 ), nonparametric ANOVAs showed significant group differences (p$$< 0.01$$ < 0.01 ). The TD and ADHD groups did not differ from each other in post-hoc analyses. With the exception of NDWR, the ASD group showed significantly (p$$< 0.01$$ < 0.01 ) lower scores than both comparison groups. The ALMs were correlated with standardized clinical and language evaluations of ASD. In age- and IQ-adjusted logistic regression analyses, four ALMs significantly predicted ASD status with satisfactory accuracy (67.9–75.5%). When ALMs were combined together, accuracy improved to 82.4%. These ALMs offer a promising approach for generating novel outcome measures.

Identifying Childhood Expressive Language Features That Best Predict Adult Language and Communication Outcome in Individuals With Autism Spectrum Disorder

Purpose Several studies have reported that “useful speech” at 5 years of age predicts outcomes in individuals with autism spectrum disorder (ASD), but this skill has been vaguely defined. This study investigates which specific aspects of expressive language in children with ASD best predict adult language and communication outcomes. Method Language samples from 29 children (ages 47–72 months) enrolled in a longitudinal project (e.g., Lord et al., 2006 ) were transcribed and coded for spoken language features. Hierarchical linear regression was used to compare the following childhood variables as predictors of adult language and communication outcomes: noun diversity, verb diversity, mean length of utterance, and proportion of utterances that were socially motivated. Results Childhood verb diversity was a value-added predictor of all four adult outcome measures (i.e., verbal IQ, Autism Diagnostic Observation Schedule Communication + Social Interaction Algorithm totals, Peabody Picture Vocabulary Test scores, and Vineland Adaptive Behavior Scales Communication Domain scores), while noun diversity and proportion of utterances that were socially motivated were not value-added predictors of any adult outcome measures. In a second set of regression analyses, mean length of utterance was substituted for verb diversity and was a value-added predictor of two out of four adult outcome measures (i.e., verbal IQ and Vineland Adaptive Behavior Scales Communication Domain scores). The pattern of findings for the other predictors remained the same as in the previous analyses. Conclusion These results have implications for our understanding of early language in ASD and for clinical decision making in early childhood.