Data processing: speech signal processing – linguistics – language – Linguistics – Translation machine
Reexamination Certificate
1998-06-26
2001-01-30
Isen, Forester W. (Department: 2747)
Data processing: speech signal processing, linguistics, language
Linguistics
Translation machine
C704S256000
Reexamination Certificate
active
06182026
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention relates to a method as recited in the preamble of claim
1
. Various earlier translation methods have been designed. A relatively simple procedure is to use a translation code book, wherein each source item, such as a word or a phrase, maps on a single destination item. Such method is only useful for simple situations. A higher level method has been disclosed in [Berger & Brown
+
94] A. L. Berger, P. F. Brown, J. Cocke, S. A. Della Pietra, V. J. Della Pietra, J. R. Gillett, J. D. Lafferty, R. L. Mercer, H. Printz, L. Ures: “The Candide System for Machine Translation”, ARPA Human Language Technology Workshop, Plainsboro, N.J., Morgan Kaufmann Publishers, San Mateo, Calif., pages 152-157, March 1994. [Brown & Pietra
+
93] P. F. Brown, S. A. Della Pietra, V. J. Della Pietra, R. L. Mercer: “Mathematics of Statistical Machine Translation: Parameter Estimation”, Computational Linguistics, Vol. 19.2, pages 263-311, June 1993. It appears that the models governing the various word sequences could be improved upon, which also should allow raising the efficiency of the search procedures. In addition, there is a need for more simple procedures that will still cater to a high percentage of texts of intermediate complexity. Now, the present inventors have recognized the potential of dynamic programming and the technology of Hidden Markov Modelling that both have been used for speech recognition, as well as recognized various aspects that speech recognition and text translation in have in common.
SUMMARY TO THE INVENTION
In consequence, amongst other things, it is an object of the present invention to use technology that has been applied to speech recognition, and now apply it in a wider context to text translation. Now therefore, according to one of its aspects the invention is characterized by the steps as recited in the characterizing part of Claim
1
. It has been found that this new field of application of dynamic programming necessitates only a relatively low level of operational complexity, while the results have been found excellent.
By itself, the use of dynamic programming in speech recognition technology has been disclosed in a series of earlier patents and patent applications assigned to the present assignee, such as U.S. Pat. No. 5,228,110, U.S. Ser. No. 08/425,304 (PHD 91136), U.S. Ser. No. 08/312,495 (PHD 91137), U.S. Ser. No. 08/563,853 (PHD 91138), U.S. Ser. No. 08/203,105 (PHD 93034) and U.S. Ser. No. 08/587,190 (PHN 15167).
The invention also relates to a device arranged for implementing the method as recited supra. Further advantageous aspects of the invention are recited in dependent Claims.
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“The Candide System for Machine Translation”, by A.L. Berger et al., ARPA Human Language Technology Workshop, Mar. 1994, pp. 152-157 (Morgan Kauffmann Publishers, San Mateo, CA).
“The Mathematics of Statistical Machine Translation Parameter Estimation”, by P.F. Brown et al, Computational Linguistics, vol. 19.2, pp. 263-311.
Ney Hermann
Tillmann Christoph
Vogel Stephan
Edouard Patrick N.
Isen Forester W.
Piotrowski Daniel J.
U.S. Philips Corporation
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