The Effect of Tone Modeling in Vietnamese LVCSR System
Tác giả
Tài liệu tham khảo
[1] Vu, T.T., Nguyen, D.T., Luong, M.C., Hosom, J.P. Vietnamese large vocabulary continuous speech recognition. In: INTERSPEECH. 2005.
[2] Vu, N.T., Schultz, T. Vietnamese large vocabulary continuous speech recognition. In: Proc. Automatic Speech Recognition and Under- standing (ASRU). Merano, Italy: IEEE; 2009.
[3] Nguyen, H.Q., Nocera, P., Castelli, E., et al. Using tone information for vietnamese continuous speech recognition. In: Research, Innovation and Vision for the Future, 2008. RIVF 2008. IEEE International Conference on. IEEE; 2008, p. 103-106.
[4] Ghahremani, P., BabaAli, B., Povey, D., Riedhammer, K., Trmal, J., Khudanpur, S. A pitch extraction algorithm tuned for automatic speech recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014. 2014, p. 2494-2498.
[5] Chuong, N.T. Selection of sentence set for vietnamese audiovisual corpus design. In: IDAACS (1). IEEE. ISBN 978-1-4577-1426-9; 2011, p. 492-495.
[6] Vu, Q., Demuynck, K., Van Compernolle, D. Vietnamese automatic speech recognition: The flavor approach. In: Proceedings of the 5th International Conference on Chinese Spoken Language Processing; ISCSLP’06. Berlin, Heidelberg: Springer-Verlag. ISBN 3-540-49665-3, 978-3-540-49665-6; 2006, p. 464-474.
[7] Nguyen, T., Vu, Q. Advances in acoustic modeling for vietnamese lvcsr. In: Asian Language Processing, 2009. IALP’09. International Conference on. IEEE; 2009, p. 280-284.
[8] Nguyen, Q.B., Gehring, J., Kilgour, K., Waibel, A. Optimizing deep bottleneck feature extraction. In: Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2013 IEEE RIVF International Conference on. 2013, p. 152-156.
[9] Quang, N.H., Nocera, P., Castelli, E., Loan, T.V. A novel approach in continuous speech recognition for vietnamese. In: SLTU. 2008.
[10] Talkin, D. A robust algorithm for pitch tracking (RAPT). In: Klein, W.B., Palival, K.K., editors. Speech Coding and Synthesis. Elsevier; 1995.
[11] Plante, F., Meyer, G.F., Ainsworth, W.A. A pitch extraction reference database. In: EUROSPEECH. ISCA; 1995.
[12] Chuong, N.T. Automatic speech recognition of Vietnamese. Ph.D. thesis; Technical University of Liberec; Studentsk1402/2, 461 17 Liberec, Czech Republic; 2014.
[13] Grezl, F., Karafiat, M., Kontair, S., Cernocky, J. Probabilistic and bottle-neck features for lvcsr of meetings. In: Acoustics, Speech and Signal Processing (ICASSP), 2007 IEEE International Conference on. IEEE. 2007, p. V–757 – IV–760.
[14] Yu, D., Seltzer, M.L. Improved bottleneck features using pretrained deep neural networks. In: INTERSPEECH. 2011, p. 237-240.
[15] Gehring, J., Miao, Y., Metze, F., Waibel, A. Extracting deep bottleneck features using stacked auto-encoders. In: ICASSP2013. Vancouver, CA; 2013, p. 3377-3381.
[16] Povey, D., Ghoshal, A., Boulianne, G., Burget, L., Glembek, O., Goel, N., et al. The kaldi speech recognition toolkit. In: IEEE 2011 Workshop on Automatic Speech Recognition and Understanding. IEEE Signal Processing Society; 2011, IEEE Catalog No.: CFP11SRW- USB.
[17] Gales, M. Maximum likelihood linear transformations for hmm-based speech recognition. Computer Speech and Language 1998;12(2):75–98.