In this work we study how features typically used in natural language processing tasks, together with measures from syntactic complexity, can be adapted to the problem of developing language profiles of bilingual children. Our experiments show that these features can provide high discriminative value for predicting language dominance from story retells in a Spanish–English bilingual population of children. Moreover, some of our proposed features are even more powerful than measures commonly used by clinical researchers and practitioners for analyzing spontaneous language samples of children. This study shows that the field of natural language processing has the potential to make significant contributions to communication disorders and related areas.

Citation Key: solorio2011 <标题>: 分析西班牙语–英语双语儿童的语言样本以自动预测语言优势 <AI Smry>: The experiments show that features typically used in natural language processing tasks together with measures from syntactic complexity can provide high discriminative value for predicting language dominance from story retells in a Spanish–English bilingual population of children.