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    <titleInfo>
        <title>Garnishing a phonetic dictionary for ASR intake</title>
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    <name type="personal">
        <namePart type="given">Iben</namePart>
        <namePart type="given">Nyholm</namePart>
        <namePart type="family">Debess</namePart>
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    <name type="personal">
        <namePart type="given">Sandra</namePart>
        <namePart type="given">Saxov</namePart>
        <namePart type="family">Lamhauge</namePart>
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    <name type="personal">
        <namePart type="given">Peter</namePart>
        <namePart type="given">Juel</namePart>
        <namePart type="family">Henrichsen</namePart>
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        <dateIssued>2019-sep–oct</dateIssued>
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            <title>Proceedings of the 22nd Nordic Conference on Computational Linguistics</title>
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        <name type="personal">
            <namePart type="given">Mareike</namePart>
            <namePart type="family">Hartmann</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Barbara</namePart>
            <namePart type="family">Plank</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <publisher>Linköping University Electronic Press</publisher>
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    <abstract>We present a new method for preparing a lexical-phonetic database as a resource for acoustic model training. The research is an offshoot of the ongoing Project Ravnur (Speech Recognition for Faroese), but the method is language-independent. At NODALIDA 2019 we demonstrate the method (called SHARP) online, showing how a traditional lexical-phonetic dictionary (with a very rich phone inventory) is transformed into an ASR-friendly database (with reduced phonetics, preventing data sparseness). The mapping procedure is informed by a corpus of speech transcripts. We conclude with a discussion on the benefits of a well-thought-out BLARK design (Basic Language Resource Kit), making tools like SHARP possible.</abstract>
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        <url>https://aclanthology.org/W19-6147/</url>
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        <date>2019-sep–oct</date>
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            <start>395</start>
            <end>399</end>
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%0 Conference Proceedings
%T Garnishing a phonetic dictionary for ASR intake
%A Debess, Iben Nyholm
%A Lamhauge, Sandra Saxov
%A Henrichsen, Peter Juel
%Y Hartmann, Mareike
%Y Plank, Barbara
%S Proceedings of the 22nd Nordic Conference on Computational Linguistics
%D 2019
%8 sep–oct
%I Linköping University Electronic Press
%C Turku, Finland
%F debess-etal-2019-garnishing
%X We present a new method for preparing a lexical-phonetic database as a resource for acoustic model training. The research is an offshoot of the ongoing Project Ravnur (Speech Recognition for Faroese), but the method is language-independent. At NODALIDA 2019 we demonstrate the method (called SHARP) online, showing how a traditional lexical-phonetic dictionary (with a very rich phone inventory) is transformed into an ASR-friendly database (with reduced phonetics, preventing data sparseness). The mapping procedure is informed by a corpus of speech transcripts. We conclude with a discussion on the benefits of a well-thought-out BLARK design (Basic Language Resource Kit), making tools like SHARP possible.
%U https://aclanthology.org/W19-6147/
%P 395-399

Markdown (Informal)

[Garnishing a phonetic dictionary for ASR intake](https://aclanthology.org/W19-6147/) (Debess et al., NoDaLiDa 2019)

• Garnishing a phonetic dictionary for ASR intake (Debess et al., NoDaLiDa 2019)

ACL

• Iben Nyholm Debess, Sandra Saxov Lamhauge, and Peter Juel Henrichsen. 2019. Garnishing a phonetic dictionary for ASR intake. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 395–399, Turku, Finland. Linköping University Electronic Press.