Statistical Relational Learning With Unconventional String Models.

This paper shows how methods from statistical relational learning can be used to address problems in grammatical inference using model-theoretic representations of strings. These model-theoretic representations are the basis of representing formal languages logically. Conventional representations include a binary relation for order and unary relations describing mutually exclusive properties of each position in the string. This paper presents experiments on the learning of formal languages, and their stochastic counterparts, with unconventional models, which relax the mutual exclusivity condition. Unconventional models are motivated by domain-specific knowledge. Comparison of conventional and unconventional word models shows that in the domains of phonology and robotic planning and control, Markov Logic Networks With unconventional models achieve better performance and less runtime with smaller networks than Markov Logic Networks With conventional models.

Language Development in the First Year of Life: What Deaf Children Might Be Missing Before Cochlear Implantation.

OBJECTIVES: Language development is a multifaceted, dynamic process involving the discovery of complex patterns, and the refinement of native language competencies in the context of communicative interactions. This process is already advanced by the end of the first year of life for hearing children, but prelingually deaf children who initially lack a language model may miss critical experiences during this early window. The purpose of this review is twofold. First, we examine the published literature on language development during the first 12 months in typically developing children. Second, we use this literature to inform our understanding of the language outcomes of prelingually deaf children who receive cochlear implants (CIs), and therefore language input, either before or after the first year. CONCLUSIONS: During the first 12 months, typically developing infants exhibit advances in speech segmentation, word learning, syntax acquisition, and communication, both verbal and nonverbal. Infants and their caregivers coconstruct a communication foundation during this time, supporting continued language growth. The language outcomes of hearing children are robustly predicted by their experiences and acquired competencies during the first year; yet these predictive links are absent among prelingually deaf infants lacking a language model (i.e., those without exposure to sign). For deaf infants who receive a CI, implantation timing is crucial. Children receiving CIs before 12 months frequently catch up with their typically developing peers, whereas those receiving CIs later do not. Explanations for the language difficulties of late-implanted children are discussed.