URI | http://purl.tuc.gr/dl/dias/A626F192-FFCC-4C9F-B53E-E0F41DB33825 | - |
Αναγνωριστικό | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=326617 | - |
Αναγνωριστικό | https://doi.org/10.1109/89.326617 | - |
Γλώσσα | en | - |
Μέγεθος | 8 pages | en |
Τίτλος | Training issues and channel equalization techniques for the construction of telephone acoustic models using a high-quality speech corpus | en |
Δημιουργός | Neumeyer Leonardo | en |
Δημιουργός | Digalakis Vasilis | en |
Δημιουργός | Διγαλακης Βασιλης | el |
Δημιουργός | Weintraub M. | en |
Εκδότης | Institute of Electrical and Electronics Engineers | en |
Περίληψη | We describe an approach for the estimation of acoustic phonetic models that will be used in a hidden Markov model (HMM) recognizer operating over the telephone. We explore two complementary techniques to developing telephone acoustic models. The first technique presents two new channel compensation algorithms. Experimental results on the Wall Street Journal corpus show no significant improvement over sentence-based cepstral-mean removal. The second technique uses an existing “high-quality” speech corpus to train acoustic models that are appropriate for the switchboard credit card task over long-distance telephone lines. Experimental results show that cross-database acoustic training yields performance similar to that of conventional task-dependent acoustic training | en |
Τύπος | Peer-Reviewed Journal Publication | en |
Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2015-11-02 | - |
Ημερομηνία Δημοσίευσης | 1994 | - |
Θεματική Κατηγορία | Automatic speech recognition | en |
Βιβλιογραφική Αναφορά | L. Neumeyer, V. Digalakis and M. Weintraub, "Training issues and channel equalization techniques for the construction of telephone acoustic models using a high-quality speech corpus," IEEE Trans. Speech Audio Process., vol. 2, no. 4, pp. 590-597, Oct. 1994. doi:10.1109/89.326617 | en |