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Towards Unsupervised Learning for Handwriting Recognition Michał Kozielski, Malte Nuhn, Patrick Doetsch, Hermann Ney Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen Univer
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Jeju / Trento / Washington / DC / Sofia / Barcelona / Bari / /

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International Journal / Vf / Human Language Technologies / Las Vegas NV / Google / OSEO / SIEMENS / /

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United States / Italy / Bulgaria / South Korea / Spain / /

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Event

Reorganization / /

Facility

University of Massachusetts / Pattern Recognition Group Computer Science Department RWTH Aachen University / /

IndustryTerm

multi-dimensional neural network / recurrent neural networks / tree search strategy / neural networks / search concepts / utilized cipher breaking algorithms / relaxation algorithm / search space / handwritten mail processing / /

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Speech / /

Organization

Assoc. for Computational Linguistics / University of Massachusetts / Amherst / Pattern Recognition Group Computer Science Department RWTH Aachen University / French State / Analysis and Machine Intelligence / Association for Computational Linguistics / /

Person

Hermann Ney / /

Position

representative / /

Product

Mauser / HMMs / Altec XT1 Speakers / /

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DC / /

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Massachusetts / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / Computational Linguistics / /

Technology

utilized cipher breaking algorithms / speech recognition / OCR / Natural Language Processing / neural network / machine translation / Viterbi algorithm / relaxation algorithm / optical character recognition / /

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