Iterative Transformation and Alignment for Speech Labeling
Identifieur interne : 001226 ( Crin/Curation ); précédent : 001225; suivant : 001227Iterative Transformation and Alignment for Speech Labeling
Auteurs : Y. Gong ; J.-P. HatonSource :
English descriptors
- KwdEn :
Abstract
We address the problem of labeling phonemes in a large database of spoken sentences using a different, already labeled utterance of each sentence. In labeling an utterance, a time alignment between the utterance and a reference utterance is required. This alignment compares parameter vectors from different speakers and is therefore subject to an acoustic mismatch. The accuracy of conventional alignment methods which do not deal with the cross-speaker mismatch is thus limited. We improve speech database labeling by iterating two steps : alignment against the labeled speech and transformation of parameter vectors from test to reference. We propose to use a linear scalar transform for each component of a parameter vector. Under our experimental conditions, the results showed that the misalignment between the reference and test utterances was reduced, and the improved alignment improved the recognition rate. A recognition system trained using the phonetic labels provided by iteration of the alignment process gave a 50========percnt; reduction in sentence recognition error rate.
Links toward previous steps (curation, corpus...)
- to stream Crin, to step Corpus: Pour aller vers cette notice dans l'étape Curation :001226
Links to Exploration step
CRIN:gong93eLe document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" wicri:score="415">Iterative Transformation and Alignment for Speech Labeling</title></titleStmt><publicationStmt><idno type="RBID">CRIN:gong93e</idno><date when="1993" year="1993">1993</date><idno type="wicri:Area/Crin/Corpus">001226</idno><idno type="wicri:Area/Crin/Curation">001226</idno><idno type="wicri:explorRef" wicri:stream="Crin" wicri:step="Curation">001226</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Iterative Transformation and Alignment for Speech Labeling</title><author><name sortKey="Gong, Y" sort="Gong, Y" uniqKey="Gong Y" first="Y." last="Gong">Y. Gong</name></author><author><name sortKey="Haton, J P" sort="Haton, J P" uniqKey="Haton J" first="J.-P." last="Haton">J.-P. Haton</name></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>speech labeling</term><term>speech recognition</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en" wicri:score="2939">We address the problem of labeling phonemes in a large database of spoken sentences using a different, already labeled utterance of each sentence. In labeling an utterance, a time alignment between the utterance and a reference utterance is required. This alignment compares parameter vectors from different speakers and is therefore subject to an acoustic mismatch. The accuracy of conventional alignment methods which do not deal with the cross-speaker mismatch is thus limited. We improve speech database labeling by iterating two steps : alignment against the labeled speech and transformation of parameter vectors from test to reference. We propose to use a linear scalar transform for each component of a parameter vector. Under our experimental conditions, the results showed that the misalignment between the reference and test utterances was reduced, and the improved alignment improved the recognition rate. A recognition system trained using the phonetic labels provided by iteration of the alignment process gave a 50========percnt; reduction in sentence recognition error rate.</div></front></TEI><BibTex type="inproceedings"><ref>gong93e</ref><crinnumber>93-R-230</crinnumber><category>3</category><equipe>RFIA</equipe><author><e>Gong, Y.</e><e>Haton, J.-P.</e></author><title>Iterative Transformation and Alignment for Speech Labeling</title><booktitle>{Proceedings of European Conference on Speech Communication and Technology, Berlin, Germany}</booktitle><year>1993</year><volume>3</volume><pages>1759-1762</pages><month>sep</month><keywords><e>speech labeling</e><e>speech recognition</e></keywords><abstract>We address the problem of labeling phonemes in a large database of spoken sentences using a different, already labeled utterance of each sentence. In labeling an utterance, a time alignment between the utterance and a reference utterance is required. This alignment compares parameter vectors from different speakers and is therefore subject to an acoustic mismatch. The accuracy of conventional alignment methods which do not deal with the cross-speaker mismatch is thus limited. We improve speech database labeling by iterating two steps : alignment against the labeled speech and transformation of parameter vectors from test to reference. We propose to use a linear scalar transform for each component of a parameter vector. Under our experimental conditions, the results showed that the misalignment between the reference and test utterances was reduced, and the improved alignment improved the recognition rate. A recognition system trained using the phonetic labels provided by iteration of the alignment process gave a 50========percnt; reduction in sentence recognition error rate.</abstract></BibTex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Lorraine/explor/InforLorV4/Data/Crin/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001226 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Crin/Curation/biblio.hfd -nk 001226 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Lorraine
|area= InforLorV4
|flux= Crin
|étape= Curation
|type= RBID
|clé= CRIN:gong93e
|texte= Iterative Transformation and Alignment for Speech Labeling
}}
| This area was generated with Dilib version V0.6.33. |  |