Extension du vocabulaire d’un système de transcription avec de nouveaux noms propres en utilisant un corpus diachronique
Identifieur interne : 000A87 ( Main/Exploration ); précédent : 000A86; suivant : 000A88Extension du vocabulaire d’un système de transcription avec de nouveaux noms propres en utilisant un corpus diachronique
Auteurs : Irina Illina [France] ; Dominique Fohr [France] ; Georges Linares [France]Source :
English descriptors
Abstract
Proper names are usually keys to understand the information contained in a document. Our work focuses on increasing the vocabulary size of a speech transcription system by automatically retrieving proper names from contemporary diachronic text documents. We proposed methods that dynamically augment the automatic speech recognition system vocabulary, using lexical and temporal features. We assume that the same proper names frequently appear in documents relating to the same time period. We studied a method based on Mutual Information and we proposed a new method based on cosine similarity to retrieve new proper names. In this new method, proper name context is represented by vector space model (Bag of Words). We also studied different metrics for proper name selection in order to limit the vocabulary augmentation and therefore the impact on the ASR performances. Recognition results show a significant reduction of the word error rate using augmented vocabulary with retrieved proper names.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région), Provence-Alpes-Côte d'Azur
- Avignon, Metz, Nancy
- Université d'Avignon, Université de Lorraine
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 005C08
- to stream Hal, to step Curation: 005C08
- to stream Hal, to step Checkpoint: 000A24
- to stream Main, to step Merge: 000A89
- to stream Main, to step Curation: 000A87
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 keys to understand the information contained in a document. Our work focuses on increasing the vocabulary size of a speech transcription system by automatically retrieving proper names from contemporary diachronic text documents. We proposed methods that dynamically augment the automatic speech recognition system vocabulary, using lexical and temporal features. We assume that the same proper names frequently appear in documents relating to the same time period. We studied a method based on Mutual Information and we proposed a new method based on cosine similarity to retrieve new proper names. In this new method, proper name context is represented by vector space model (Bag of Words). We also studied different metrics for proper name selection in order to limit the vocabulary augmentation and therefore the impact on the ASR performances. Recognition results show a significant reduction of the word error rate using augmented vocabulary with retrieved proper names.</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>Metz</li><li>Nancy</li></settlement><orgName><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= Extension du vocabulaire d’un système de transcription avec de nouveaux noms propres en utilisant un corpus diachronique
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