Core vocabulary is a set of words that are stable used across different text types, theme, and application scenario. In natural language, the number of core vocabulary is relatively small, the core vocabulary, however, plays an important part in language learning because it constitutes a major part of communication content. The traditional core vocabulary selection method is mainly based on the...

Results of recent computational modelling studies suggest that a general function of the striatum in human cognition is related to shifting decision criteria in selection processes. We used functional magnetic resonance imaging (fMRI) in 21 healthy subjects to examine the hemodynamic responses when subjects shift their response criterion on a trial-by-trial basis in the lexical decision paradig...

We suggest a new goal and evaluation criterion for word similarity measures. The new criterion meaning-entailing substitutability fits the needs of semantic-oriented NLP applications and can be evaluated directly (independent of an application) at a good level of human agreement. Motivated by this semantic criterion we analyze the empirical quality of distributional word feature vectors and its...

This paper presents an integrated tool to construct and maintain translation-memory for memory-based machine translation. This tool was aimed to automate constructing and validating translation-memory both in word and in phrase levels from English-Thai parallel texts. To align English-Thai words and phrases, the crucial problems that must be resolved include multiple-word-expression boundary am...

How does the presence of a categorically related word influence picture naming latencies? In order to test competitive and noncompetitive accounts of lexical selection in spoken word production, we employed the picture-word interference (PWI) paradigm to investigate how conceptual feature overlap influences naming latencies when distractors are category coordinates of the target picture. Mahon ...

The paper proposes that expanded and improved treatment of morphological information is both needed and newly possible in electronic English dictionaries, including dictionaries for native speakers. The focus is dictionary selection, treatment, and presentation of derived words. Inconsistencies and inadequacies can be attributed not only to print’s legacy, but also to assumptions about native s...

A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features. Word sense disambiguation improves many Natural Language Processing (NLP) applications such as Information Retrieval, Information Extraction, Machine Translation, or Lexical Simplification. Roughly speaking, the aim is to choose for each word in a text its best sense. One of the most popul...

Real-word spelling correction differs from non-word spelling correction in its aims and its challenges. Here we show that the central problem in real-word spelling correction is detection. Methods from non-word spelling correction, which focus instead on selection among candidate corrections, do not address detection adequately, because detection is either assumed in advance or heavily constrai...

In this experiment using a color-word Stroop task, we explored whether different regions of prefrontal cortex bias selection of response-related processes as compared with non-response-related processes. To manipulate demands at the level of response selection, we varied the degree of overlap between stimulus-response mappings in a manual Stroop task. To vary demands at a non-response level, we...