The Test of Word Finding (TWF 2). (A pilot study and validation in Greek pre school aged children & data for word retrieval in this population) Tafiadis Dionysios, Stamatina Larentzaki, Despoina Magioglou, Ioannis Mpourakis, Maria Neofotistou, Aggeliki Pagoni, Ellisavet Xatiefremidou, Maria Tafiadi From 1 International Congress on Neurobiology and Clinical Psychopharmacology and European Psychi...

Word sense disambiguation is the task to identify the intended meaning of an ambiguous word in a certain context, one of the central problems in natural language processing. This paper describes four novel supervised disambiguation methods which adapt some familiar algorithms. They built on the Vector Space Model using an automatically generated stop list and two different statistical methods o...

Quantitative assessment of 50 patients with closed head injury disclosed that anomic errors and word finding difficulty were prominent sequelae as nearly half of the series had defective scores on tests of naming and/or word association. Aphasic disturbance was associated with severity of brain injury as reflected by prolonged coma and injury of the brain stem.

This paper deals with a subword-unit-based isolated word recognition system with enhanced speaker-independency. The subword is defined as a part of word whose central portion has rather stationary or time-invariant short-time spectra with its portions near its ends having rapidly varying short-time spectra. In this system each isolated word is decomposed into a sequence of subwords, each of whi...

In Tibetan, as words are written consecutively without delimiters, finding unknown word boundary is difficult. This paper presents a hybrid approach for Tibetan unknown word identification for offline corpus processing. Firstly, Tibetan named entity is preprocessed based on natural annotation. Secondly, other Tibetan unknown words are extracted from word segmentation fragments using MTC, the co...

A word may have multiple senses and the challenge is to find out which particular sense is appropriate in a given context. Word sense disambiguation(WSD) resolves this ambiguity by finding out which particular sense of a word is appropriate in a given context. WSD is of critical importance in the areas of machine translation, information retrieval, speech processing etc. In this paper we presen...

The existing word representation methods mostly limit their information source to word co-occurrence statistics. In this paper, we introduce ngrams into four representation methods: SGNS, GloVe, PPMI matrix, and its SVD factorization. Comprehensive experiments are conducted on word analogy and similarity tasks. The results show that improved word representations are learned from ngram cooccurre...

At about 7 months of age, infants listen longer to sentences containing familiar words - but not deviant pronunciations of familiar words (Jusczyk & Aslin, 1995). This finding suggests that infants are able to segment familiar words from fluent speech and that they store words in sufficient phonological detail to recognize deviations from a familiar word. This finding does not examine whether i...

Bargh, Chaiken, Raymond, and Hymes (1996) and Hermans, De Houwer, and Eelen (1994) showed that a valenced target word is pronounced faster after the presentation of an affectively related prime word than after the presentation of an affectively unrelated prime word. This finding is important because it provides crucial evidence for the hypotheses that stimulus evaluation (a) is goal-independent...

Word Sense Disambiguation (WSD) is considered as one of the toughest problem in the field of Natural Language Processing. IndoWordNet is a linked structure of WordNets of major Indian languages. Recently, several IndoWordNet based WSD approaches have been proposed and implemented for Indian languages. In this chapter, we present the usage of various other features of IndoWordNet in performing W...