We present an ACT-R model of signal-to-respond lexical decision. This model is based on a mental lexicon constructed from a complete list of English four-letter words with associated word frequencies. A number of (signal-to-respond) lexical decision phenomena are explained by the model, without having to rely on mechanisms specific to lexical decision. Besides explaining these phenomena, the mo...

We describe a mechanism for the generation of lexical paraphrases of queries posed to an Internet resource. These paraphrases are generated using WordNet and part-of-speech information to propose synonyms for the content words in the queries. Statistical information, obtained from a corpus, is then used to rank the paraphrases. We evaluated our mechanism using 404 queries whose answers reside i...

The role of lexical resources is often understated in NLP research. The complexity of Chinese, Japanese and Korean (CJK) poses special challenges to developers of NLP tools, especially in the area of word segmentation (WS), information retrieval (IR), named entity extraction (NER), and machine translation (MT). These difficulties are exacerbated by the lack of comprehensive lexical resources, e...

Children with language impairments demonstrate a broad range of semantic difficulties, including problems with new word acquisition, storage and organization of known words, and lexical access/ retrieval. Unfortunately, assessments of children's semantic skills are often limited to measures of receptive and expressive vocabulary size. As a result, the semantic deficits of these children may not...

This article describes an algorithm called HyperLex that is capable of automatically determining word uses in a textbase without recourse to a dictionary. The algorithm makes use of the specific properties of word cooccurrence graphs, which are shown as having "small world" properties. Unlike earlier dictionary-free methods based on word vectors, it can isolate highly infrequent uses (as rare a...

In a typical lexical decision task, participants are asked to categorize visually presented letter strings as either existing words or as “nonwords”. The most straightforward findings in lexical decision studies are (1) that high frequency words (“house”, “girl”) and nonwords which are not similar to existing words (“yebe”) are responded to more accurately than low frequency words (“chute”, “li...

The role of lexical resources is often understated in NLP research. The complexity of Chinese, Japanese and Korean (CJK) poses special challenges to developers of NLP tools, especially in the area of word segmentation (WS), information retrieval (IR), named entity extraction (NER), and machine translation (MT). These difficulties are exacerbated by the lack of comprehensive lexical resources, e...

Contributive resources, such as Wikipedia, have proved to be valuable to Natural Language Processing or multilingual Information Retrieval applications. This work focusses on Wiktionary, the dictionary part of the resources sponsored by the Wikimedia foundation. In this article, we present our effort to extract multilingual lexical data from Wiktionary data and to provide it to the community as...

Multiple studies (Galati & Brennan, 2014; Hoetjes, Koolen, Goudbeek, Krahmer, & Swerts, 2001; Jacobs & Garnham, 2007) have shown reduction in co-speech gesture across repetition. Reduction can be interpreted in terms of demonstrating automatization of effort (Vajrabhaya & Pederson, 2014). This study specifically investigates a special type of gesture used when speakers are accessing a low-famil...