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- W2291723904 abstract "Lexicon-based handwritten text keyword spotting (KWS) has proven to be a faster and more accurate alternative to lexicon-free methods. Nevertheless, since lexicon-based KWS relies on a predefined vocabulary, fixed in the training phase, it does not support queries involving out-of-vocabulary (OOV) keywords. In this paper, we outline previous work aimed at solving this problem and present a new approach based on smoothing the (null) scores of OOV keywords by means of the information provided by “similar” in-vocabulary words. Good results achieved using this approach are compared with previously published alternatives on different data sets." @default.
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- W2291723904 date "2016-02-03" @default.
- W2291723904 modified "2023-09-25" @default.
- W2291723904 title "Querying out-of-vocabulary words in lexicon-based keyword spotting" @default.
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- W2291723904 doi "https://doi.org/10.1007/s00521-016-2197-8" @default.
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