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Computing Lexical Contrast     Computing Lexical  Contrast       font style='font-size:12px;'> 2015/9/11
Knowing the degree of semantic contrast between words has widespread application in natural language processing, including machine translation, information retrieval, and dialogue systems. Manually cr...
A Scalable Distributed Syntactic,Semantic,and Lexical Language Model     Distributed  Syntactic  Semantic  Lexical       font style='font-size:12px;'> 2015/9/10
This paper presents an attempt at building a large scale distributed composite language model that is formed by seamlessly integrating an n-gram model, a structured language model, and probabilistic l...
Automatically Identifying the Source Words of Lexical Blends in English     English  Lexical Blends       font style='font-size:12px;'> 2015/9/8
Newly coined words pose problems for natural language processing systems because they are not in a system’s lexicon, and therefore no lexical information is available for such words. A common way to...
Choosing the wrong word in a machine translation or natural language generation system can convey unwanted connotations, implications, or attitudes. The choice between near-synonyms such as error, m...
The quantification of lexical semantic relatedness has many applications in NLP, and many different measures have been proposed. We evaluate five of these measures, all of which use Word...
We present a methodology for extracting subcategorization frames based on an automaticlexical-functional grammar (LFG) f-structure annotation algorithm for the Penn-II and Penn-III Treebanks. We extra...
Techniques that exploit knowledge of distributional similarity between words have been proposed in many areas of Natural Language Processing. For example, in language modeling, the sparse data problem...
Near-Synonymy and Lexical Choice     Near-Synonymy  Lexical Choice       font style='font-size:12px;'> 2015/8/27
We develop a new computational model for representing the fine-grained meanings of near-synonyms and the differences between them. We also develop a lexical-choice process that can decide which of sev...
While automatic text summarization is an area that has received a great deal of attention in recent research, the problem of efficiency in this task has not been frequently addressed. When the ...
Human Variation and Lexical Choice     Human Variation  Lexical Choice       font style='font-size:12px;'> 2015/8/27
Much natural language processing research implicitly assumes that word meanings are fixed in a language community, but in fact there is good evidence that different people probably associate s...
In this book Hunston and Francis describe an approach to lexical and grammatical description that was used to produce two remarkable Collins COBUILD reference works, Grammar Patterns 1: Verbs and Gram...
We present a probabilistic model that uses both prosodic and lexical cues for the automatic segmentation of speech into topically coherent units. We propose two methods for combining lexical and proso...
In contrast, a state-of-the-art natural language generation (NLG) system would likely be able to produce only one of them, modulo variations introduced by, for example, passivization, topicalization,...
When (computational) linguists speak of “lexical semantics,” quite often they are actually referring to the more narrow area of verb semantics. Similarly, this book chooses the fairly abstract title ...
Linguistic categories have been shown to influence perceptual discrimination, to do so preferentially in the right visual field, to fail to do so when competing demands are made on verbal memory, and ...

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