Proper Name Retrieval from Diachronic Documents for Automatic Speech Transcription using Lexical and Temporal Context
Identifieur interne : 000954 ( Main/Exploration ); précédent : 000953; suivant : 000955Proper Name Retrieval from Diachronic Documents for Automatic Speech Transcription using Lexical and Temporal Context
Auteurs : Irina Illina [France] ; Dominique Fohr [France] ; Georges Linares [France]Source :
English descriptors
Abstract
Proper names are usually key to understanding the information contained in a document. Our work focuses on increasing the vocabulary coverage of a speech transcription system by automatically retrieving new proper names from contemporary diachronic text documents. The idea is to use in-vocabulary proper names as an anchor to collect new linked proper names from the diachronic corpus. Our assumption is that time is an important feature for capturing name-to-context dependencies, that was confirmed by temporal mismatch experiments. We studied a method based on Mutual Information and proposed a new method based on cosine-similarity measure that dynamically augment the automatic speech recognition system vocabulary. Recognition results show a significant reduction of the word error rate using augmented vocabulary for broadcast news transcription.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région), Provence-Alpes-Côte d'Azur
- Avignon, Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université d'Avignon, Université de Lorraine
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 003D98
- to stream Hal, to step Curation: 003D98
- to stream Hal, to step Checkpoint: 000889
- to stream Main, to step Merge: 000955
- to stream Main, to step Curation: 000954
Le document en format XML
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84 029 Avignon cedex 1</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-avignon.fr/</ref></desc></org></tutelle><tutelle active="#struct-302221" type="direct"><org type="institution" xml:id="struct-302221" status="VALID"><orgName>Centre d'Enseignement et de Recherche en Informatique - CERI</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Avignon</settlement><region type="region" nuts="2">Provence-Alpes-Côte d'Azur</region></placeName><orgName type="university">Université d'Avignon</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>out-of-vocabulary words</term><term>proper names</term><term>speech recognition</term><term>vocabulary augmentation</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Proper names are usually key to understanding the information contained in a document. Our work focuses on increasing the vocabulary coverage of a speech transcription system by automatically retrieving new proper names from contemporary diachronic text documents. The idea is to use in-vocabulary proper names as an anchor to collect new linked proper names from the diachronic corpus. Our assumption is that time is an important feature for capturing name-to-context dependencies, that was confirmed by temporal mismatch experiments. We studied a method based on Mutual Information and proposed a new method based on cosine-similarity measure that dynamically augment the automatic speech recognition system vocabulary. Recognition results show a significant reduction of the word error rate using augmented vocabulary for broadcast news transcription.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li><li>Provence-Alpes-Côte d'Azur</li></region><settlement><li>Avignon</li><li>Nancy</li></settlement><orgName><li>Institut national polytechnique de Lorraine</li><li>Université Nancy 2</li><li>Université d'Avignon</li><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="Illina, Irina" sort="Illina, Irina" uniqKey="Illina I" first="Irina" last="Illina">Irina Illina</name></region><name sortKey="Fohr, Dominique" sort="Fohr, Dominique" uniqKey="Fohr D" first="Dominique" last="Fohr">Dominique Fohr</name><name sortKey="Linares, Georges" sort="Linares, Georges" uniqKey="Linares G" first="Georges" last="Linares">Georges Linares</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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|texte= Proper Name Retrieval from Diachronic Documents for Automatic Speech Transcription using Lexical and Temporal Context
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