Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.

Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification of language disorders in children.

Method: We first describe the current barriers to clinicians' use of language sample analysis, narrative language sampling approaches, and the data processing stages that precede analysis.

Sign language experience has little effect on face and biomotion perception in bimodal bilinguals.

Sensory and language experience can affect brain organization and domain-general abilities. For example, D/deaf individuals show superior visual perception compared to hearing controls in several domains, including the perception of faces and peripheral motion. While these enhancements may result from sensory loss and subsequent neural plasticity, they may also reflect experience using a visual-manual language, like American Sign Language (ASL), where signers must process moving hand signs and facial cues simultaneously.

White matter correlates of reading subskills in children with and without reading disability.

Individual differences in reading ability are associated with characteristics of white matter microstructure in the brain. However, previous studies have largely measured reading as a single construct, resulting in difficulty characterizing the role of structural connectivity in discrete subskills of reading. The present study used diffusion tensor imaging to examine how white matter microstructure, measured by fractional anisotropy (FA), relates to individual differences in reading subskills in children aged 8 to 14 (n = 65).

Chinese-English bilinguals are more sensitive to environmental sound perception than Spanish-English bilinguals through top-down cognitive mechanism.

Sensitive perception to environmental sound is important for an individual's daily life since it helps in responding to the environment quickly and avoiding potential risks. It remains unclear, however, whether and how bilingual experiences with different native language backgrounds influence brain responses reflecting environmental sound perception. The present study compared Chinese-English bilinguals, Spanish-English bilinguals, and English monolinguals on their brain response to environmental sound perception and further examined its processing mechanism.

Second Language Immersion Experience Could Help the Brain Response to Second Language Reading for Native Chinese Speakers.

Native language background exerts constraints on the individual's brain automatic response while learning a second language. It remains unclear, however, whether second language immersion experience could help the brain overcome such constraints and meet the requirements of a second language. This study compared native Chinese speakers with English-as-a-second-language immersion experience (immersive English learners), native Chinese speakers without English-as-a-second-language immersion experience (nonimmersive English learners), and native English speakers with an ERP cross-modal MMN paradigm.