Discriminative training of decoding graphs for large vocabulary continuous speech recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 4, Issue , 2007, Pages

  Kuo, Hong Kwang Jeff ^a   Kingsbury, Brian ^a   Zweig, Geoffrey ^b  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

Discriminative training; Finite state decoding graph; Language model; Low resource speech recognition; Pronunciation model

Indexed keywords

DISCRIMINATIVE TRAINING; FINITE-STATE DECODING GRAPH; LANGUAGE MODEL; PRONUNCIATION MODEL;

BROADCASTING; DECISION TREES; FINITE AUTOMATA; REAL TIME SYSTEMS; SIGNAL ENCODING; SPEECH RECOGNITION;

GRAPH THEORY;

EID: 34547515916     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.367159     Document Type: Conference Paper

References (14)

1. Mehryar Mohri, Fernando Pereira, and Michael Riley, "Weighted finite-state transducers in speech recognition," Computer Speech and Language, vol. 16, no. 1, pp. 69-88, 2002.
2. Andreas Stoleke and Mitch Weintraub, "Discriminative language modeling," in Proc. 9th Hub-5 Conversational Speech Recognition Workshop, 1998.
3. Hong-Kwang Jeff Kuo, Eric Fosler-Lussier, Hui Jiang, and Chin-Hui Lee, "Discriminative training of language models for speech recognition," in Proc. ICASSP 2002, Orlando, Florida, May 2002.
4. Vaibhava Goel, "Conditional maximum likelihood estimation for improving annotation performance of N-gram models incorporating stochastic finite state grammars," in Proc. ICSLP 2004, Jeju Island, Korea, Oct. 2004.
5. Brian Roark, Murat Saraclar, and Michael Collins, "Discriminative n-gram language modeling," Computer Speech and Language, 2006, to appear.
6. Brian Roark, Murat Saraclar, Michael Collins, and Mark Johnson, "Discriminative language modeling with conditional random fields and the perceptron algorithm," in Proc. ACL, Barcelona, Spain, July 2004.
7. Shiuan-Sung Lin and François Yvon, "Discriminative training of finite state decoding graphs," in Proc. Interspeech 2005, Lisbon, Portugal, Sept. 2005.
8. Shigeru Katagiri, Chin-Hui Lee, and Biing-Hwang Juang, "New discriminative algorithm based on the generalized probabilistic descent method," in Proc. IEEE Workshop on Neural Network for Signal Processing, Princeton, Sept. 1991, pp. 299-309.
9. Biing-Hwang Juang, Wu Chou, and Chin-Hui Lee, "Minimum classification error rate methods for speech recognition," IEEE Transactions on Speech and Audio Processing, vol. 5, no. 3, pp. 257-265, May 1997.
10. Stanley F. Chen, "Compiling large-context phonetic decision trees into finite-state transducers," in Proc. Eurospeech 2003, Geneva, Switzerland, Sept. 2003.
11. Stanley F. Chen, "The IBM finite-state machine toolkit," Tech. Rep., IBM T.J. Watson Research Center, Feb. 2000.
12. Mehryar Mohri, Fernando C. Pereira, and Michael Riley, "AT&T Finite-State Machine Library," http://www.research.att.com/Tsmtools/fsm/.
13. Jonathan Le Roux and Eric McDermott, "Optimization methods for discriminative training," in Proc. Interspeech 2005, Lisbon, Portugal, Sept. 2005.
14. Scott E. Fahlman, "An empirical study of learning speed in back-propagation networks," Tech. Rep. CMU-CS-88-162, Carnegie Mellon University, Sept. 1998.