URI | http://purl.tuc.gr/dl/dias/564BB011-677C-4372-A3C3-F66DEACE053D | - |
Αναγνωριστικό | http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=536930&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D536930 | - |
Αναγνωριστικό | https://doi.org/10.1109/89.536930 | - |
Γλώσσα | en | - |
Μέγεθος | 19 pages | en |
Τίτλος | From HMM's to segment models: a unified view of stochastic modeling for speech recognition | en |
Δημιουργός | Ostendorf M. | en |
Δημιουργός | Digalakis Vasilis | en |
Δημιουργός | Διγαλακης Βασιλης | el |
Δημιουργός | Kimball O. | en |
Εκδότης | Institute of Electrical and Electronics Engineers | en |
Περίληψη | Many alternative models have been proposed to address some of the shortcomings of the hidden Markov model (HMM), which is currently the most popular approach to speech recognition. In particular, a variety of models that could be broadly classified as segment models have been described for representing a variable-length sequence of observation vectors in speech recognition applications. Since there are many aspects in common between these approaches, including the general recognition and training problems, it is useful to consider them in a unified framework. The paper describes a general stochastic model that encompasses most of the models proposed in the literature, pointing out similarities of the models in terms of correlation and parameter tying assumptions, and drawing analogies between segment models and HMMs. In addition, we summarize experimental results assessing different modeling assumptions and point out remaining open questions | 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 | 1996 | - |
Θεματική Κατηγορία | HMM | en |
Θεματική Κατηγορία | Hidden Markov Model | en |
Θεματική Κατηγορία | Speech recognition | en |
Βιβλιογραφική Αναφορά | M. Ostendorf, V. Digalakis and O. Kimball, "From HMM's to segment models: a unified view of stochastic modeling for speech recognition," IEEE Trans. Speech Audio Process., vol. 4, no. 5, pp. 360-378, Sep. 1996. doi:10.1109/89.536930 | en |