Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...

This thesis describes a computational model of child language acquisition which acquires a recursive phrase-structure grammar in the absence of X-Bar Theory. The model assumes no grammar, lexicon, or segmentation. Input utterances include phrases as well as sentences, of no more than two levels of embedding, paired with their semantic representations. The initial products of acquisition are a l...

INTRODUCTION Although attention deficit hyperactivity disorder (ADHD) is usually associated with language disorders, there are few studies of phonological processing and the efficacy of psychostimulants (methylphenidate) on this. OBJECTIVE 1. To find whether there are differences in the development of phonological processing, evaluated using linguistic segmentation tests and tests of lexical ...

Over the past couple of decades, research has established that infants are sensitive to the predominant stress pattern of their native language. However, the degree to which the stress pattern shapes infants' language development has yet to be fully determined. Whether stress is merely a cue to help organize the patterns of speech or whether it is an important part of the representation of spee...

We present ongoing work in linguistic processing of hashtags in Twitter text, with the goal of supplying normalized hashtag content to be used in more complex natural language processing (NLP) tasks. Hashtags represent collectively shared topic designators with considerable surface variation that can hamper semantic interpretation. Our normalization scripts allow for the lexical consolidation a...

In this paper we present the results of experiments comparing (a) rich syntactic and semantic feature sets and (b) big context windows, for the TempEval time expression and event segmentation and classification tasks. We show that it is possible for models using only lexical features to approach the performance of models using rich syntactic and semantic feature sets.

We introduce a novel topic segmentation approach that combines evidence of topic shifts from lexical cohesion with linguistic evidence such as syntactically distinct features of segment initial contributions. Our evaluation demonstrates that this hybrid approach outperforms state-of-the-art algorithms even when applied to loosely structured, spontaneous dialogue.

In spoken language systems, the segmentation of utterances into coherent linguistic/semantic units is required when modules following the speech recognizer can only process such units one at a time. In this paper, techniques for semantic boundary prediction, based on both acoustic and lexical knowledge, are presented and tested on a corpus of personto-person dialogues. Best result gives 62.8% r...

We propose a framework for analyzing episodic conversational activities in terms of expressed relationships between the participants and utterance content. We test the hypothesis that linguistic features which express such properties, e.g. tense, aspect, and person deixis, are a useful basis for automatic intentional discourse segmentation. We present a novel algorithm and test our hypothesis o...

The word is the basic unit in natural language processing (NLP), as it is at the lexical level upon which further processing rests. The lack of word delimiters such as spaces in Chinese texts makes Chinese word segmentation (CWS) an interesting while challenging issue. This paper describes the in-depth research following our participation in the fourth International Chinese Language Processing ...