Context and spoken word recognition in a novel lexicon.

[Correction Notice: An erratum for this article was reported in Vol 35(1) of Journal of Experimental Psychology: Learning, Memory, and Cognition (see record 2008-18581-022). Figure 9 was inadvertently duplicated as Figure 10. Figure 9 in the original article was correct. The correct Figure 10 is provided.] Three eye movement studies with novel lexicons investigated the role of semantic context in spoken word recognition, contrasting 3 models: restrictive access, access-selection, and continuous integration. Actions directed at novel shapes caused changes in motion (e.g., looming, spinning) or state (e.g., color, texture). Across the experiments, novel names for the actions and the shapes varied in frequency, cohort density, and whether the cohorts referred to actions (Experiment 1) or shapes with action-congruent or action-incongruent affordances (Experiments 2 and 3). Experiment 1 demonstrated effects of frequency and cohort competition from both displayed and non-displayed competitors. In Experiment 2, a biasing context induced an increase in anticipatory eye movements to congruent referents and reduced the probability of looks to incongruent cohorts, without the delay predicted by access-selection models. In Experiment 3, context did not reduce competition from non-displayed incompatible neighbors as predicted by restrictive access models. The authors conclude that the results are most consistent with continuous integration models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于语义分类的比较句识别与比较要素抽取研究

比较是人们常用的评估不同事物优劣、异同的表达方式,利用机器识别比较句并进一步抽取比较要素是语言信息处理领域一项新颖又有实用价值的课题。该文依据比较句与比较要素之间是一种“你中有我,我中有你”的共生关系,将比较句识别与比较要素抽取两个任务合二为一完成;根据词意分类,构建由领域词典、情感词典、标记词典、普通词典构成的词典系统;根据汉语比较句句义分类,构建比较句识别与比较要素抽取规则库。以第四届中文倾向性评测(COAE2012)发布的测试语料为实验对象,该系统取得了较好的实验(评测)结果。     

The time course of spoken word learning and recognition: Studies with artificial lexicons.

The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

一种基于图的情感基准词选择方法

作为文本情感分析的前提和基础,词语的情感极性判别显得尤为重要。现有利用情感基准词进行词语的情感倾向研究中,情感基准词的选择多数基于研究者的人工判别或词语的使用频率。以上方式存在着随机性和主观性的缺陷,并且难以保证对词典中语义关系的全面覆盖。本文提出以候选基准词为顶点,两词间的知网相似度作为边的权重设定参数来构建情感词的无向图。将图中结点的中介性值作为基准词的选择依据,从而保证所选基准词的可靠性。实验证明,通过该方法选取出来的基准词在词的情感倾向分类中具有较高的准确率。     

"Context and spoken word recognition in a novel lexicon": Correction.

Reports an error in "Context and spoken word recognition in a novel lexicon" by Kathleen Pirog Revill, Michael K. Tanenhaus and Richard N. Aslin (Journal of Experimental Psychology: Learning, Memory, and Cognition, 2008[Sep], Vol 34[5], 1207-1223). Figure 9 was inadvertently duplicated as Figure 10. Figure 9 in the original article was correct. The correct Figure 10 is provided. (The following abstract of the original article appeared in record 2008-11850-014.) Three eye movement studies with novel lexicons investigated the role of semantic context in spoken word recognition, contrasting 3 models: restrictive access, access-selection, and continuous integration. Actions directed at novel shapes caused changes in motion (e.g., looming, spinning) or state (e.g., color, texture). Across the experiments, novel names for the actions and the shapes varied in frequency, cohort density, and whether the cohorts referred to actions (Experiment 1) or shapes with action-congruent or action-incongruent affordances (Experiments 2 and 3). Experiment 1 demonstrated effects of frequency and cohort competition from both displayed and non-displayed competitors. In Experiment 2, a biasing context induced an increase in anticipatory eye movements to congruent referents and reduced the probability of looks to incongruent cohorts, without the delay predicted by access-selection models. In Experiment 3, context did not reduce competition from non-displayed incompatible neighbors as predicted by restrictive access models. The authors conclude that the results are most consistent with continuous integration models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Accademia della Crusca: New perspectives in lexicography

The Accademia della Crusca is involved in historical, philological and lexicographical research into the Italian language. First, we provide some background information on the Accademia. Second, we discuss the problems of selectivity and inertia of nineteenth century lexicography, and define modern day requirements. We then consider the contribution of the computer to modern lexicography, and some computer-based dictionary projects, including those undertaken specifically at the Accademia. Giovanni Nencioni is the President of the Accademia della Crusca (Florence, Italy), quondam professor of Italian linguistics in the Scuola Normale Superiore, Pisa. His main research interests are the history of the literary Italian language and lexicography. He has two major publications: Tra grammatica e retorica, Torino: Einaudi Paperbacks, 1983; and Saggi di lingua antica e moderna, Torino: Rosenberg e Sellier, 1989.     

Construction of a Chinese–English Verb Lexicon for Machine Translation and Embedded Multilingual Applications

This paper addresses the problem of automatic acquisition of lexical knowledge for rapid construction of engines for machine translation and embedded multilingual applications. We describe new techniques for large-scale construction of a Chinese–English verb lexicon and we evaluate the coverage and effectiveness of the resulting lexicon. Leveraging off an existing Chinese conceptual database called How Net and a large, semantically rich English verb database, we use thematic-role information to create links between Chinese concepts and English classes. We apply the metrics of recall and precision to evaluate the coverage and effectiveness of the linguistic resources. The results of this work indicate that: (a) we are able to obtain reliable Chinese–English entries both with and without pre-existing semantic links between the two languages; (b) if we have pre-existing semantic links, we are able to produce a more robust lexical resource by merging these with our semantically rich English database; (c) in our comparisons with manual lexicon creation, our automatic techniques were shown to achieve 62% precision, compared to a much lower precision of 10% for arbitrary assignment of semantic links. This revised version was published online in November 2006 with corrections to the Cover Date.     

单词语义相似性计算综述

研究了单词语义相似性计算方法,其中基于知识的方法和基于语料的方法是两种主要方法。这两种方法及其融合方法都把单词看成一个整体,主要利用单词外部信息进行语义相似性计算。近些年,出现了一些利用单词内部信息进行单词语义相似性计算的工作,它们使用汉字、部首、词根、词缀等来计算单词语义相似性。利用单词的内部结构解析,解决从细粒度到粗粒度的语义相似性推导,最终计算出单词间的语义相似性是单词语义相似性计算的必然阶段。当从外部信息转向内部信息时,可以改善已有单词语义相似性计算的性能,尤其是为低频词或未登录词的准确语义相似性计算提供了可能性。