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    <titleInfo>
        <title>Language Model Based Chinese Handwriting Address Recognition</title>
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    <name type="personal">
        <namePart type="given">Chieh-Jen</namePart>
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        <namePart type="given">Yung-Ping</namePart>
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        <namePart type="given">Yun-Wei</namePart>
        <namePart type="family">Hung</namePart>
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            <title>Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)</title>
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            <publisher>The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)</publisher>
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    <abstract>Chinese handwritten address recognition of consignment note is an important challenge of smart logistics automation. Chinese handwritten characters detection and recognition is the key technology for this application. Since the writing mode of handwritten characters is more complex and diverse than printed characters, it is easy misjudgment for recognition. Moreover, the address text occupies a small proportion in the image of the consignment note and arranged closely, which is easy to cause difficulties in detection. Therefore, how to detect the address text on the consignment note accurately is a focus of this paper. The consignment note address automatic detection and recognition system proposed in this paper detects and recognizes address characters, reduces the probability of misjudgment of Chinese handwriting recognition through language model, and improves the accuracy.</abstract>
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        <url>https://aclanthology.org/2022.rocling-1.1</url>
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        <date>2022-11</date>
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            <start>1</start>
            <end>6</end>
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%0 Conference Proceedings
%T Language Model Based Chinese Handwriting Address Recognition
%A Wang, Chieh-Jen
%A Tien, Yung-Ping
%A Hung, Yun-Wei
%S Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)
%D 2022
%8 November
%I The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
%C Taipei, Taiwan
%G Chinese
%F wang-etal-2022-language
%X Chinese handwritten address recognition of consignment note is an important challenge of smart logistics automation. Chinese handwritten characters detection and recognition is the key technology for this application. Since the writing mode of handwritten characters is more complex and diverse than printed characters, it is easy misjudgment for recognition. Moreover, the address text occupies a small proportion in the image of the consignment note and arranged closely, which is easy to cause difficulties in detection. Therefore, how to detect the address text on the consignment note accurately is a focus of this paper. The consignment note address automatic detection and recognition system proposed in this paper detects and recognizes address characters, reduces the probability of misjudgment of Chinese handwriting recognition through language model, and improves the accuracy.
%U https://aclanthology.org/2022.rocling-1.1
%P 1-6

Markdown (Informal)

[Language Model Based Chinese Handwriting Address Recognition](https://aclanthology.org/2022.rocling-1.1) (Wang et al., ROCLING 2022)

• Language Model Based Chinese Handwriting Address Recognition (Wang et al., ROCLING 2022)

ACL

• Chieh-Jen Wang, Yung-Ping Tien, and Yun-Wei Hung. 2022. Language Model Based Chinese Handwriting Address Recognition. In Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022), pages 1–6, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).