A Level-Building Top-Down Parsing Algorithm for Context-Free Grammars in Continuous Speech Recognition
Identifieur interne : 000274 ( Hal/Corpus ); précédent : 000273; suivant : 000275A Level-Building Top-Down Parsing Algorithm for Context-Free Grammars in Continuous Speech Recognition
Auteurs : François Charpillet ; Joseph Di MartinoSource :
English descriptors
Abstract
We present in this paper a dynamic programming parsing algorithm in the framework of continuous speech recognition. The language of the applications we want to deal with, is described using a context-free grammar given in Greibach normal form. The parsing algorithm follows the level-building technique and finds the p sentences matching the speech signal with the best scores. Our approach is different from the existing ones, in the sense that it is suboptimal but with a lower order of complexity. By suboptimal we mean that a syntactically correct sentence with a score belonging to the p best ones can be missed by our algorithm. This leads us to discuss the trade-off between quality of results on the one hand and the complexity of the algorithm on the other hand. As a conclusion, we will see that in practice, our approach yields results of comparable quality in spite of their slight theoritical corruption.
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<front><div type="abstract" xml:lang="en">We present in this paper a dynamic programming parsing algorithm in the framework of continuous speech recognition. The language of the applications we want to deal with, is described using a context-free grammar given in Greibach normal form. The parsing algorithm follows the level-building technique and finds the p sentences matching the speech signal with the best scores. Our approach is different from the existing ones, in the sense that it is suboptimal but with a lower order of complexity. By suboptimal we mean that a syntactically correct sentence with a score belonging to the p best ones can be missed by our algorithm. This leads us to discuss the trade-off between quality of results on the one hand and the complexity of the algorithm on the other hand. As a conclusion, we will see that in practice, our approach yields results of comparable quality in spite of their slight theoritical corruption.</div>
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<idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno>
<idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno>
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<notesStmt><note type="audience" n="2">International</note>
<note type="invited" n="0">No</note>
<note type="popular" n="0">No</note>
<note type="peer" n="1">Yes</note>
<note type="proceedings" n="1">Yes</note>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">A Level-Building Top-Down Parsing Algorithm for Context-Free Grammars in Continuous Speech Recognition</title>
<author role="aut"><persName><forename type="first">François</forename>
<surname>Charpillet</surname>
</persName>
<email>francois.charpillet@loria.fr</email>
<idno type="idHal">francois-charpillet</idno>
<idno type="halAuthorId">58657</idno>
<affiliation ref="#struct-2359"></affiliation>
</author>
<author role="aut"><persName><forename type="first">Joseph</forename>
<surname>Di Martino</surname>
</persName>
<email>jdm@loria.fr</email>
<idno type="halAuthorId">861252</idno>
<orgName ref="#struct-413289"></orgName>
<affiliation ref="#struct-2359"></affiliation>
</author>
</analytic>
<monogr><meeting><title>EUROSPEECH - Third European Conference on Speech Communication and Technology - 1993</title>
<date type="start">1993-09-22</date>
<date type="end">1993-09-25</date>
<settlement>Berlin</settlement>
<country key="DE">Germany</country>
</meeting>
<imprint><biblScope unit="pp">1947-1949</biblScope>
<date type="datePub">1993</date>
</imprint>
</monogr>
</biblStruct>
</sourceDesc>
<profileDesc><langUsage><language ident="en">English</language>
</langUsage>
<textClass><keywords scheme="author"><term xml:lang="en">Dynamic Programming</term>
<term xml:lang="en">Context-Free</term>
<term xml:lang="en">Grammars</term>
<term xml:lang="en">Continuous Speech</term>
</keywords>
<classCode scheme="halDomain" n="info.info-ts">Computer Science [cs]/Signal and Image Processing</classCode>
<classCode scheme="halDomain" n="spi.signal">Engineering Sciences [physics]/Signal and Image processing</classCode>
<classCode scheme="halTypology" n="COMM">Conference papers</classCode>
</textClass>
<abstract xml:lang="en">We present in this paper a dynamic programming parsing algorithm in the framework of continuous speech recognition. The language of the applications we want to deal with, is described using a context-free grammar given in Greibach normal form. The parsing algorithm follows the level-building technique and finds the p sentences matching the speech signal with the best scores. Our approach is different from the existing ones, in the sense that it is suboptimal but with a lower order of complexity. By suboptimal we mean that a syntactically correct sentence with a score belonging to the p best ones can be missed by our algorithm. This leads us to discuss the trade-off between quality of results on the one hand and the complexity of the algorithm on the other hand. As a conclusion, we will see that in practice, our approach yields results of comparable quality in spite of their slight theoritical corruption.</abstract>
</profileDesc>
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