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LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries

  • Algorithms for calculating the string edit distance are used in e.g. information retrieval and document analysis systems or for evaluation of text recognizers. Text recognition based on CTC-trained LSTM networks includes a decoding step to produce a string, possibly using a language model, and evaluation using the string edit distance. The decoded string can further be used as a query for database search, e.g. in document retrieval. We propose to closely integrate dictionary search with text recognition to train both combined in a continuous fashion. This work shows that LSTM networks are capable of calculating the string edit distance while allowing for an exchangeable dictionary to separate learned algorithm from data. This could be a step towards integrating text recognition and dictionary search in one deep network.

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Author:Martin Schall, Haiyan Buehrig, Marc-Peter Schambach, Matthias O. FranzORCiDGND
Parent Title (English):13th IAPR International Workshop on Document Analysis Systems, 24 - 27. April 2018, Vienna, Austria
Document Type:Conference Proceeding
Year of Publication:2018
Release Date:2019/01/08
Page Number:2
Institutes:Institut für Optische Systeme - IOS
Open Access?:Ja
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Licence (German):License LogoKeine CC-Lizenz - Es gilt der Veröffentlichungsvertrag für Publikationen