In this paper, we introduce image-based word clouds as a novel tool for a quick and aesthetic overviews of common words in collections of digitized text manuscripts. While OCR can be used to enable summaries and search functionality to printed modern text, historical and handwritten documents remains a challenge. By segmenting and counting word images, without applying manual transcription or O...

A text recognition algorithm is proposed that uses word-level language constraints in a deciphering framework to directly decode the identity of each word pattern in an input text. This is a font-independent approach that solves problems of touching characters and character fragmentation. The major difficulty of using a deciphering approach on the word level is that the existence of relatively ...

Word Autocorrelation Redundancy Match (WARM) is an intelligent facsimile technology which compresses the image of textual documents at nominally 145:l by use of complex symbol matching on both the word and character level. At the word level, the complex symbol match rate i s enhanced by the redundancy of the word image. This creates a unique image compression capability that allows a document t...

Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because linking distributional cues vs. phonological informat...

Word prediction is an important NLP problem in which we want to predict the correct word in a given context. Word completion utilities, predictive text entry systems, writing aids, and language translation are some of common word prediction applications. This paper presents a new word prediction approach based on context features and machine learning. The proposed method casts the problem as a ...

Word spotting is to make searchable unindexed image documents by locating word/words in a doc-ument image, given a query word. This problem is challenging, mainly due to the large numberof word classes with very small inter-class and substantial intra-class distances. In this paper, asegmentation-based word spotting method is presented for multi-writer Persian handwritten doc-...