Burst segmentation and evaluation of acoustic cues
Identifieur interne : 005E62 ( Hal/Checkpoint ); précédent : 005E61; suivant : 005E63Burst segmentation and evaluation of acoustic cues
Auteurs : Yves Laprie [France] ; Anne Bonneau [France]Source :
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Abstract
This paper investigates burst segmentation for the evaluation of acoustic cues used to identify unvoiced French stops. Unlike other works which utilize a fixed length window, our approach consists in segmenting bursts into transient and frication noise. The transient is found by minimizing the sum of spectral variances of transient and frication noise over the burst. The spectral variance criterion has the advantage of being sensitive both to energy deviations and spectral variations. Additional correction procedures augment the robustness of the segmentation against the presence of spurious noises during the closure and the determination of the voicing onset with delay. The relevance of our segmentation method has been evaluated by comparing the characteristics of the main spectral peak (energy prominence versus frequency) in the transient segmented by our method with those of the full burst. Our experiments showed that bursts segmented by our method allow a better discrimination between the three places of articulation.
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Hal:inria-00100475Le document en format XML
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French stops. Unlike other works which utilize a fixed length window, our approach consists in segmenting bursts into transient and frication noise. The transient is found by minimizing the sum of spectral variances of transient and frication noise over the burst. The spectral variance criterion has the advantage of being sensitive both to energy deviations and spectral variations. Additional correction procedures augment the robustness of the segmentation against the presence of spurious noises during the closure and the determination of the voicing onset with delay. The relevance of our segmentation method has been evaluated by comparing the characteristics of the main spectral peak (energy prominence versus frequency) in the transient segmented by our method with those of the full burst. Our experiments showed that bursts segmented by our method allow a better discrimination between the three places of articulation.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Burst segmentation and evaluation of acoustic cues</title><author role="aut"><persName><forename type="first">Yves</forename><surname>Laprie</surname></persName><email></email><idno type="idhal">yves-laprie</idno><idno type="halauthor">129874</idno><orgName ref="#struct-441569"></orgName><affiliation ref="#struct-2359"></affiliation></author><author role="aut"><persName><forename type="first">Anne</forename><surname>Bonneau</surname></persName><email>Anne.Bonneau@loria.fr</email><idno type="halauthor">130180</idno><orgName ref="#struct-441569"></orgName><affiliation ref="#struct-2359"></affiliation></author><editor role="depositor"><persName><forename>Publications</forename><surname>Loria</surname></persName><email>publications@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2006-09-26 14:46:04</date><date type="whenModified">2016-05-18 08:54:01</date><date type="whenReleased">2006-09-28 15:22:47</date><date type="whenProduced">2001</date></edition><respStmt><resp>contributor</resp><name key="108626"><persName><forename>Publications</forename><surname>Loria</surname></persName><email>publications@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00100475</idno><idno type="halUri">https://hal.inria.fr/inria-00100475</idno><idno type="halBibtex">laprie:inria-00100475</idno><idno type="halRefHtml">7th European Conference on Speech Communication and Technology - EUROSPEECH'2001, 2001, Aalborg, Danemark, 1, 4 p, 2001</idno><idno type="halRef">7th European Conference on Speech Communication and Technology - EUROSPEECH'2001, 2001, Aalborg, Danemark, 1, 4 p, 2001</idno></publicationStmt><seriesStmt><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="INRIA2">INRIA 2</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="commentary">Colloque avec actes et comité de lecture. internationale.</note><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></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Burst segmentation and evaluation of acoustic cues</title><author role="aut"><persName><forename type="first">Yves</forename><surname>Laprie</surname></persName><idno type="idHal">yves-laprie</idno><idno type="halAuthorId">129874</idno><orgName ref="#struct-441569"></orgName><affiliation ref="#struct-2359"></affiliation></author><author role="aut"><persName><forename type="first">Anne</forename><surname>Bonneau</surname></persName><email>Anne.Bonneau@loria.fr</email><idno type="halAuthorId">130180</idno><orgName ref="#struct-441569"></orgName><affiliation ref="#struct-2359"></affiliation></author></analytic><monogr><idno type="localRef">A01-R-092 || laprie01a</idno><meeting><title>7th European Conference on Speech Communication and Technology - EUROSPEECH'2001</title><date type="start">2001</date><settlement>Aalborg, Danemark</settlement></meeting><imprint><biblScope unit="volume">1</biblScope><biblScope unit="pp">4 p</biblScope><date type="datePub">2001</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="fr">stops</term><term xml:lang="fr">automatic segmentation</term><term xml:lang="fr">strong acoustic cues</term><term xml:lang="fr">segmentation automatique</term><term xml:lang="fr">burst onset</term><term xml:lang="fr">indices acoustiques forts</term><term xml:lang="fr">occlusives</term></keywords><classCode scheme="halDomain" n="info.info-oh">Computer Science [cs]/Other [cs.OH]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">This paper investigates burst segmentation for the evaluation of acoustic cues used to identify unvoiced French stops. Unlike other works which utilize a fixed length window, our approach consists in segmenting bursts into transient and frication noise. The transient is found by minimizing the sum of spectral variances of transient and frication noise over the burst. The spectral variance criterion has the advantage of being sensitive both to energy deviations and spectral variations. Additional correction procedures augment the robustness of the segmentation against the presence of spurious noises during the closure and the determination of the voicing onset with delay. The relevance of our segmentation method has been evaluated by comparing the characteristics of the main spectral peak (energy prominence versus frequency) in the transient segmented by our method with those of the full burst. Our experiments showed that bursts segmented by our method allow a better discrimination between the three places of articulation.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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