Speech recognition system, training arrangement and method...

Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C704S236000, C704S231000

Reexamination Certificate

active

07010486

ABSTRACT:
The invention relates to a speech recognition system and a method of calculating iteration values for free parameters λαortho(n)of a maximum-entropy speech model MESM with the aid of the generalized-iterative scaling training algorithm in a computer-supported speech recognition system in accordance with the formula λαortho(n+1)=G(λαortho(n), mαortho, . . . ), where n is an iteration parameter, G a mathematical function, α an attribute in the MESM and mαorthoa desired orthogonalized boundary value in the MESM for the attribute α. It is an object of the invention to further develop the system and method so that they make a fast computation of the free parameters λ possible without a change of the original training object. According to the invention this object is achieved in that the desired orthogonalized boundary value mαorthois calculated by a linear combination of the desired boundary value mαwith desired boundary values mβfrom attributes β that have a larger range than the attribute α. mαand mβare then desired boundary values of the original training object.

REFERENCES:
patent: 6304841 (2001-10-01), Berger et al.
Adam Berger, The Improved Iterative Scalling Algorithm: A Gentle Introduction, Dec., 1997, http://citeseer.nj.nec.com/31826.html.
Chen, S., Rosenfeld, Ronald. “Efficient Sampling and Feature Selection in Whole Sentence Maximum Entropy Language Models”, Acoustics, Speech and Signal Processing, ICASSP-99, IEEE Conference on, vol. 1, Mar. 15-19, 1999, pp. 549-552.
Beyerlein, Peter. “Discrimitive Model Combination”, Automatic Speech Recognition and Understanding, IEEE Workshop on, Dec. 14-17, 1997, pp. 238-245.
Simons, M., Ney, H., Martin, S.C. “Distant Bigram Language Modeling Using Maximum Entropy”, Acoustics, Speech and Signal Processing, ICASSP-97, IEEE Conference on, vol. 2, Apr. 21-24, pp. 787-790.
Peters, Jochen. Dietrich, Klakow. “Compact Maximum Entropy Language Models”, Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding, Dec. 1999.□□.
Kneser, Reinhard. Peters, Jochen. “Semantic Clustering for Adaptive Language Modeling”, Acoustics, Speech and Signal Processing, vol. 2, pp. 779-782, 1997.□□.
Berger, Adam L. Della Pietra, Vincent J. Della Pietra, Stephan A. “A Maximum Entropy Approach to Natural Language Processing” Computational Linguistics vol. 22, Mar. 1996.□□.
Mikheev, Andrei. “Feature Lattices for Maximum Entropy Modelling” International Conference on Computational Linguistics vol. 2, pp. 848-854 1998.□□.
Greiff, Warren R. Ponte, Jay M. “The Maximum Entropy Approach and Probabilistic IR Models” ACM Transactions on Information Systems, vol. 18, pp. 246-287, Jul. 2000.
By J.N. Darroch & D. Ratcliff, Entitled: “Generalized Iterative Scaling for Log Linear Models” Annals Math. Stat., 43(5): 1972, 1470-1480.
By R. Rosenfeld Entitled: “A Maximum-Entropy Approach to Adaptive Statistical Language Modeling”; Computer Speech and Language, 10: pp. 187-228, 1996.
R.Rosenfeld, “A Maximum Entropy Approach to Adaptive Statistical Language Modelling;” Computer Speech and Language, 1996, Academic Press Limited; 4 pgs.
J.N.Darroch et al., “Generalized Iterative Scaling For Log-Linear Models;” The Annals of Mathematical Statistics, vol. 43, No. 5; 1972; 10 pgs.
By J.N. Darroch & D. Ratcliff, Entitled: “Generalized Iterative Scaling for Log Linear Models” Annals Math. Stat., 43(5): 1972, 1470-1480, no month or day.
By R. Rosenfeld Entitled: “A Maximum-Entropy Approach to Adaptive Statistical Language Modeling”; Computer Speech and Language, 10: pp. 187-228, 1996, no month or day.
R.Rosenfeld, “A Maximum Entropy Approach to Adaptive Statistical Language Modelling;” Computer Speech and Language, 1996, Academic Press Limited; 4 pgs, no month or day.
J.N.Darroch et al., “Generalized Iterative Scaling For Log-Linear Models;” The Annals of Mathematical Statistics, vol. 43, No. 5; 1972; 10 pgs, no month or day.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Speech recognition system, training arrangement and method... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Speech recognition system, training arrangement and method..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Speech recognition system, training arrangement and method... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3557369

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.