WordSeg: Standardizing unsupervised word form segmentation from text.

A basic task in first language acquisition likely involves discovering the boundaries between words or morphemes in input where these basic units are not overtly segmented. A number of unsupervised learning algorithms have been proposed in the last 20 years for these purposes, some of which have been implemented computationally, but whose results remain difficult to compare across papers. We created a tool that is open source, enables reproducible results, and encourages cumulative science in this domain.

The role of the striatum in linguistic selection: Evidence from Huntington's disease and computational modeling.

Though accumulating evidence indicates that the striatum is recruited during language processing, the specific function of this subcortical structure in language remains to be elucidated. To answer this question, we used Huntington's disease as a model of striatal lesion. We investigated the morphological deficit of 30 early Huntington's disease patients with a novel linguistic task that can be modeled within an explicit theory of linguistic computation.

A description of externally recorded womb sounds in human subjects during gestation.

Objective: Reducing environmental noise benefits premature infants in neonatal intensive care units (NICU), but excessive reduction may lead to sensory deprivation, compromising development. Instead of minimal noise levels, environments that mimic intrauterine soundscapes may facilitate infant development by providing a sound environment reflecting fetal life. This soundscape may support autonomic and emotional development in preterm infants.

Variation in the input: a case study of manner class frequencies.

ABSTRACT What are the sources of variation in the input, and how much do they matter for language acquisition? This study examines frequency variation in manner-of-articulation classes in child and adult input. The null hypothesis is that segmental frequency distributions of language varieties are unigram (modelable by stationary, ergodic processes), and that languages are unitary (modelable as a single language variety). Experiment I showed that English segments are not unigram; they exhibit a 'bursty' distribution in which the local frequency varies more than expected by chance alone.

Learning diphone-based segmentation.

This paper reconsiders the diphone-based word segmentation model of Cairns, Shillcock, Chater, and Levy (1997) and Hockema (2006), previously thought to be unlearnable. A statistically principled learning model is developed using Bayes' theorem and reasonable assumptions about infants' implicit knowledge. The ability to recover phrase-medial word boundaries is tested using phonetic corpora derived from spontaneous interactions with children and adults.

Linking speech errors and phonological grammars: Insights from Harmonic Grammar networks.

Phonological grammars characterize distinctions between relatively well-formed (unmarked) and relatively ill-formed (marked) phonological structures. We review evidence that markedness influences speech error probabilities. Specifically, although errors result in both unmarked as well as marked structures, there is a markedness asymmetry: errors are more likely to produce unmarked outcomes.