The purpose of a word spotting system is to detect a certain set of keywords in continuous speech. The most common approach consists of models of the keywords augmented with \ ller," or \garbage" models, that are trained to account for non-keyword speech and background noise. Another approach is to use a large vocabulary continuous speech recognition system (LVCSR) to produce the most likely hy...

abstract in this study we have used the monthly data resulted from the calculation of temperature and precipitation for a 52-year period (1951-2003). the doubling effect of carbon dioxide ( ) on temperature and precipitation was modeled as the most important climatic parameters. the resulting hythergraph and ambrothermic models for tabriz indicate monthly increases of temperature and precipitat...

Diierent instances of a handwritten word consist of the same basic features (humps, cusps, crossings, etc.) arranged in a deformable spatial pattern. Thus, keywords in cursive text can be detected by looking for the appropriate features in the \correct" spatial conng-uration. A keyword can be modeled hierarchically as a set of word fragments, each of which consists of lower-level features. To a...

Keyword extraction attracts much attention for its significant role in various natural language processing tasks. While some existing methods for keyword extraction have considered using single type of semantic relatedness between words or inherent attributes of words, almost all of them ignore two important issues: 1) how to fuse multiple types of semantic relations between words into a unifor...

In recent years, many private corporations and government organizations have digitized corpuses of legacy paper documents. Often, these organizations hope to take advantage of digital representations to transform costly manual tasks associated with paper archives into less-costly computer-assisted tasks. The most common approach toward automated information extraction is through inverted indexi...