Incorporating knowledge sources into statistical speech recognition
Incorporating Knowledge Sources into Statistical Speech Recognition offers solutions for enhancing the robustness of a statistical automatic speech recognition (ASR) system by incorporating various additional knowledge sources while keeping the training and recognition effort feasible. The authors p...
שמור ב:
| Auteurs principaux: | , , , |
|---|---|
| פורמט: | Livre numérique |
| שפה: | Anglais |
| יצא לאור: |
New York, NY :
Springer US
[20..].
Cham : Springer Nature |
| מהדורה: | 1st ed. 2009. |
| סדרה: | Lecture Notes in Electrical Engineering
42 |
| גישה מקוונת: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| הערה: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Incorporating Knowledge Sources into Statistical Speech Recognition, Texte imprimé, 9780387858296 |
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| 100 | 1 | |a Minker, Wolfgang, |d 1967- | |
| 245 | 1 | 0 | |a Incorporating knowledge sources into statistical speech recognition |c by Wolfgang Minker, Satoshi Nakamura, Konstantin Markov, Sakriani Sakti. |
| 250 | |a 1st ed. 2009. | ||
| 260 | |a New York, NY : |b Springer US. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Lecture Notes in Electrical Engineering |v 42 |x 1876-1119 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a and Book Overview Statistical Speech Recognition Graphical Framework to Incorporate Knowledge Sources Speech Recognition Using GFIKS Conclusions and Future Directions | |
| 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 Incorporating Knowledge Sources into Statistical Speech Recognition offers solutions for enhancing the robustness of a statistical automatic speech recognition (ASR) system by incorporating various additional knowledge sources while keeping the training and recognition effort feasible. The authors provide an efficient general framework for incorporating knowledge sources into state-of-the-art statistical ASR systems. This framework, which is called GFIKS (graphical framework to incorporate additional knowledge sources), was designed by utilizing the concept of the Bayesian network (BN) framework. This framework allows probabilistic relationships among different information sources to be learned, various kinds of knowledge sources to be incorporated, and a probabilistic function of the model to be formulated. Incorporating Knowledge Sources into Statistical Speech Recognition demonstrates how the statistical speech recognition system may incorporate additional information sources by utilizing GFIKS at different levels of ASR. The incorporation of various knowledge sources, including background noises, accent, gender and wide phonetic knowledge information, in modeling is discussed theoretically and analyzed experimentally | ||
| 700 | 1 | |a Markov, Konstantin. |4 aut | |
| 700 | 1 | |a Nakamura, Satoshi, |d 19..- |4 aut | |
| 700 | 1 | |a Sakti, Sakriani, |d 19..- |4 aut | |
| 776 | 0 | |t Incorporating Knowledge Sources into Statistical Speech Recognition |b Texte imprimé |z 9780387858296 | |
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