Robust adaptation to non-native accents in automatic speech recognition
Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness of this technology to non-native accents, which still cause considerable difficulties for current systems. In this book, methods to overcome this problem are descri...
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| Format: | Livre numérique |
| Sprache: | Anglais |
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Berlin [etc.] :
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| Schriftenreihe: | Lecture notes in computer science. Lecture notes in artificial intelligence
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| Edition sous un autre format: | • Robust adaptation to non-native accents in automatic speech recognition, Silke Goronzy, Berlin, Springer, 2002, 1 vol. (XI-144 p.), Lecture notes in computer science, 3-540-00325-8 • Robust Adaptation to Non-Native Accents in Automatic Speech Recognition, Texte imprimé, 9783662205549 |
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| 100 | 1 | |a Goronzy, Silke, |d 19..- | |
| 245 | 1 | 0 | |a Robust adaptation to non-native accents in automatic speech recognition |c Silke Goronzy. |
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| 505 | 0 | |a ASR:AnOverview -- Pre-processing of the Speech Data -- Stochastic Modelling of Speech -- Knowledge Bases of an ASR System -- Speaker Adaptation -- Confidence Measures -- Pronunciation Adaptation -- Future Work -- Summary -- Databases and Experimental Settings -- MLLR Results -- Phoneme Inventory. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness of this technology to non-native accents, which still cause considerable difficulties for current systems. In this book, methods to overcome this problem are described. A speaker adaptation algorithm that is capable of adapting to the current speaker with just a few words of speaker-specific data based on the MLLR principle is developed and combined with confidence measures that focus on phone durations as well as on acoustic features. Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using non-native data is described and combined with the previous techniques to produce a robust adaptation to non-native accents in an automatic speech recognition system. | ||
| 650 | |a Informatique | ||
| 650 | |a Intelligence artificielle | ||
| 650 | |a Reconnaissance automatique de la parole | ||
| 650 | |a Traitement automatique du langage naturel | ||
| 650 | |a Interfaces utilisateur (informatique) | ||
| 650 | |a Logique symbolique et mathématique | ||
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| 776 | 0 | |t Robust Adaptation to Non-Native Accents in Automatic Speech Recognition |b Texte imprimé |z 9783662205549 | |
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