The comprehension and production of Wh- questions among Malay children with developmental language disorders: Climbing the syntactic tree.

This study is an investigation of both comprehension and production of Wh- questions in Malay-speaking children with a developmental language disorder (DLD). A total of 15 Malay children with DLD (ages 7;0-9;11 years) were tested on a set of Wh- questions (who subject and object, which subject and object), comparing their performance with two control groups [15 age-matched typically developing (TD) children and 15 younger TD language-matched children]. Malay children with DLD showed a clear asymmetry in comprehension of Wh- questions, with a selective impairment for which NP questions compared with who questions. Age-matched controls performed at ceiling in all Wh- questions, while the language-matched group reported a subject/object asymmetry selective for the which NP, as reported in other languages. In production, both children with DLD and younger children showed a preference for questions with in situ Wh- elements, a structure that is allowed in colloquial Malay, but which is not produced by the age-matched TD group. Several non-adult-like strategies were adopted particularly by the children with DLD to avoid complex sentences, including substitution with yes/no echo questions, production of the wrong Wh- question, and use of a generic Wh- element. The study provides an insight on the mastery of Wh- questions in both typical Malay children and children with DLD. Implications for the definition of a clinical marker for DLD in a free word order language with Wh- in situ option will be discussed.

A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric Association, is a neurodevelopmental disorder that includes deficits of social communication and social interaction with the presence of restricted and repetitive behaviors. Children with ASD have difficulties in joint attention and social reciprocity, using non-verbal and verbal behavior for communication. Due to these deficits, children with autism are often socially isolated. Researchers have emphasized the importance of early identification and early intervention to improve the level of functioning in language, communication, and well-being of children with autism. However, due to limited local assessment tools to diagnose these children, limited speech-language therapy services in rural areas, etc., these children do not get the rehabilitation they need until they get into compulsory schooling at the age of seven years old. Hence, efficient approaches towards early identification and intervention through speedy diagnostic procedures for ASD are required. In recent years, advanced technologies like machine learning have been used to analyze and investigate ASD to improve diagnostic accuracy, time, and quality without complexity. These machine learning methods include artificial neural networks, support vector machines, a priori algorithms, and decision trees, most of which have been applied to datasets connected with autism to construct predictive models. Meanwhile, the selection of features remains an essential task before developing a predictive model for ASD classification. This review mainly investigates and analyzes up-to-date studies on machine learning methods for feature selection and classification of ASD. We recommend methods to enhance machine learning's speedy execution for processing complex data for conceptualization and implementation in ASD diagnostic research. This study can significantly benefit future research in autism using a machine learning approach for feature selection, classification, and processing imbalanced data.

Targeting Complex Orthography in the Treatment of a Bilingual Aphasia with Acquired Dysgraphia: The Case of a Malay/English Speaker with Conduction Aphasia.

BACKGROUND: Disruption of spoken language in people with aphasia tends to interfere with the ability to write, which is referred to as dysgraphia. This study examined the effectiveness of the anagram and copy treatment (ACT), administered in English on a bilingual Malay/English patient with conduction aphasia (GM). ACT is the arrangement of component letters presented in scrambled order (i.e., an anagram) so that the patient could use the letters to form target words, followed by repeated copying of the word. METHODS: A single-subject multiple-baseline design was used with sets of English words (both nouns and verbs) sequentially targeted for treatment. Prior to the treatment, a series of single word writing and reading baselines were conducted in two languages: English and Malay. The ACT treatment was done in English, the language reported as more dominant for reading by the patient. Probes assessing generalizations to untrained pictures were presented at 8th, 13th, and 18th sessions. RESULTS: GM showed steady and incremental improvement in the writing of trained nouns and verbs, with generalizations to untrained English nouns and verbs. CONCLUSIONS: Single word writing treatment in a non-transparent language may improve dysgraphia among adults with bilingual aphasia through the administration of a structured and systematic treatment.

Differential coding of perception in the world's languages.

Is there a universal hierarchy of the senses, such that some senses (e.g., vision) are more accessible to consciousness and linguistic description than others (e.g., smell)? The long-standing presumption in Western thought has been that vision and audition are more objective than the other senses, serving as the basis of knowledge and understanding, whereas touch, taste, and smell are crude and of little value. This predicts that humans ought to be better at communicating about sight and hearing than the other senses, and decades of work based on English and related languages certainly suggests this is true. However, how well does this reflect the diversity of languages and communities worldwide? To test whether there is a universal hierarchy of the senses, stimuli from the five basic senses were used to elicit descriptions in 20 diverse languages, including 3 unrelated sign languages. We found that languages differ fundamentally in which sensory domains they linguistically code systematically, and how they do so. The tendency for better coding in some domains can be explained in part by cultural preoccupations. Although languages seem free to elaborate specific sensory domains, some general tendencies emerge: for example, with some exceptions, smell is poorly coded. The surprise is that, despite the gradual phylogenetic accumulation of the senses, and the imbalances in the neural tissue dedicated to them, no single hierarchy of the senses imposes itself upon language.