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FOR WORD PROCESSING
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Technical Examples
- A speech recognition system provides a subword decoder and a dictionary lookup to process a spoken input. In a first stage of processing, the subword decoder decodes the speech input based on subword units or particles and identifies hypothesized subword sequences using a particle dictionary and particle language model, but independently of a word dictionary or word vocabulary. Further stages of processing involve a particle to word graph expander and a word decoder. The particle to word graph expander expands the subword representation produced by the subword decoder into a word graph of word candidates using a word dictionary. The word decoder uses the word dictionary and a word language model to determine a best sequence of word candidates from the word graph that is most likely to match the words of the spoken input.
- Multiple recognition engines (110) provide different interpretations (116) of a word at a given location within a scanned document (108). A word node corresponding to each unique interpretation is stored within a word index (102), with each word node being linked to word nodes of previously and subsequently recognized words.
- A main computer processing system accesses a text, counts the number of times each word appears, and arranges the words on the display in a way that makes understanding the text easier. On the display, the user can see which words are used most frequently, and the placement of each word gives some information about where it appears in the text. Each word is associated with a graphical drawing that indicates everywhere the word appears in the text (a "Distribution Glyph").
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