<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="schmidt-etal-2013-using">
    <titleInfo>
        <title>Using viseme recognition to improve a sign language translation system</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Christoph</namePart>
        <namePart type="family">Schmidt</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Oscar</namePart>
        <namePart type="family">Koller</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Hermann</namePart>
        <namePart type="family">Ney</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Thomas</namePart>
        <namePart type="family">Hoyoux</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Justus</namePart>
        <namePart type="family">Piater</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2013-dec 5-6</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 10th International Workshop on Spoken Language Translation: Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Joy</namePart>
            <namePart type="given">Ying</namePart>
            <namePart type="family">Zhang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <place>
                <placeTerm type="text">Heidelberg, Germany</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Sign language-to-text translation systems are similar to spoken language translation systems in that they consist of a recognition phase and a translation phase. First, the video of a person signing is transformed into a transcription of the signs, which is then translated into the text of a spoken language. One distinctive feature of sign languages is their multi-modal nature, as they can express meaning simultaneously via hand movements, body posture and facial expressions. In some sign languages, certain signs are accompanied by mouthings, i.e. the person silently pronounces the word while signing. In this work, we closely integrate a recognition and translation framework by adding a viseme recognizer (“lip reading system”) based on an active appearance model and by optimizing the recognition system to improve the translation output. The system outperforms the standard approach of separate recognition and translation.</abstract>
    <identifier type="citekey">schmidt-etal-2013-using</identifier>
    <location>
        <url>https://aclanthology.org/2013.iwslt-papers.1/</url>
    </location>
    <part>
        <date>2013-dec 5-6</date>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Using viseme recognition to improve a sign language translation system
%A Schmidt, Christoph
%A Koller, Oscar
%A Ney, Hermann
%A Hoyoux, Thomas
%A Piater, Justus
%Y Zhang, Joy Ying
%S Proceedings of the 10th International Workshop on Spoken Language Translation: Papers
%D 2013
%8 dec 5 6
%C Heidelberg, Germany
%F schmidt-etal-2013-using
%X Sign language-to-text translation systems are similar to spoken language translation systems in that they consist of a recognition phase and a translation phase. First, the video of a person signing is transformed into a transcription of the signs, which is then translated into the text of a spoken language. One distinctive feature of sign languages is their multi-modal nature, as they can express meaning simultaneously via hand movements, body posture and facial expressions. In some sign languages, certain signs are accompanied by mouthings, i.e. the person silently pronounces the word while signing. In this work, we closely integrate a recognition and translation framework by adding a viseme recognizer (“lip reading system”) based on an active appearance model and by optimizing the recognition system to improve the translation output. The system outperforms the standard approach of separate recognition and translation.
%U https://aclanthology.org/2013.iwslt-papers.1/

Markdown (Informal)

[Using viseme recognition to improve a sign language translation system](https://aclanthology.org/2013.iwslt-papers.1/) (Schmidt et al., IWSLT 2013)

• Using viseme recognition to improve a sign language translation system (Schmidt et al., IWSLT 2013)

ACL

• Christoph Schmidt, Oscar Koller, Hermann Ney, Thomas Hoyoux, and Justus Piater. 2013. Using viseme recognition to improve a sign language translation system. In Proceedings of the 10th International Workshop on Spoken Language Translation: Papers, Heidelberg, Germany.