In this paper the performance of different confidence measures used for an address recognition system are evaluated. The recognition system for cursive handwritten German address words is based on hidden Markov models (HMMs). It is essential that the structure of the address (name, street, city, country) is known, so that a specific small but complete dictionary can be selected. Upon choosing a wrong dictionary (OOV: out-of-vocabulary) or misrecognizing a word, the recognition result should be rejected by means of the confidence measure. This paper points out two aspects: the comparison of four confidence measures for single words - based on the likelihood, a garbage-model, a two-best recognition or a character decoding - and the comparison of using complete or wrong dictionaries. It is shown that the best confidence measure - the two-best distance - has a quite different behavior using OOV.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Confidence measures for an address reading system


    Contributors:
    Brakensiek, A. (author) / Rottland, J. (author) / Rigoll, G. (author)


    Publication date :

    2003-01-01


    Size :

    260639 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Confidence Measures for an Address Reading System

    Brakensiek, A. / Rottland, J. / Rigoll, G. et al. | British Library Conference Proceedings | 2003


    MIMA MARITIME CONFIDENCE-BUILDING MEASURES

    Mak, J. N. / Council for Security Cooperation in the Asia Pacific | British Library Conference Proceedings | 1999


    Adaptive stereo similarity fusion using confidence measures

    Saygili, G. / van der Maaten, L. / Hendriks, E. A. | British Library Online Contents | 2015


    Postal Address Finding and Reading

    Srihari, S. | British Library Online Contents | 1990