Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition
Reexamination Certificate
2007-08-21
2007-08-21
Hudspeth, David (Department: 2626)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Recognition
Reexamination Certificate
active
10288517
ABSTRACT:
A model generation unit (17) is provided. The model generation unit includes an alignment module (80) arranged to receive pairs of sequences of parameter frame vectors from a buffer (16) and to perform dynamic time warping of the parameter frame vectors to align corresponding parts of the pair of utterances. A consistency checking module (82) is provided to determine whether the aligned parameter frame vectors correspond to the same word. If this is the case the aligned parameter frame vectors are passed to a clustering module (84) which groups the parameter frame vectors into a number of clusters. Whilst clustering the parameter frame vectors, the clustering module (80) determines for each grouping an objective function calculating the best fit of a model to the clusters per degrees of freedom of that model. When the best fit per degrees of freedom is determined, the parameter frame vectors are passed to a hidden Markov model generator (86) which generates a hidden Markov model having states corresponding to the clusters determined to have the best fit per degrees of freedom.
REFERENCES:
patent: 5839105 (1998-11-01), Ostendorf et al.
patent: 5873061 (1999-02-01), Häb-Umbach et al.
patent: 5895448 (1999-04-01), Vysotsky et al.
patent: 5950158 (1999-09-01), Wang
patent: 6240389 (2001-05-01), Keiller et al.
patent: 2002/0173953 (2002-11-01), Frey et al.
patent: WO 02/29612 (2002-04-01), None
Daniel Gildea, et al., “Applying Pronunciation Modeling Techniques To French”, International Computer Science Institute, University of California at Berkeley, Berkeley, CA.
Jay J. Lee, et al., “Data-driven Design of HMM Topology for On-Line Handwriting Recognition”, Dept. of Electrical Engineering & Computer Science, KAIST, Taejon, Korea, pp. 1-14.
Rabiner, et al., “Fundamentals of Speech Recognition”, Prentice Hall Signal Processing Series, Chapter 6, pp. 382-384 (1993).
“Automatically Finding The Number of States in a Video Sequence”, Computer Vision Group, Computer Science, University of Bonn, Adaptive Background Modeling Using a Hidden Markov Model, http://www-dbv.informatik.uni-bonn.de/Video/page—3.html.
Finesso, Lorenzo, “The Complexity of Hidden Markov Models”, ERCIM News Online Edition, http://www.ercim.org/publication/Ercim—News/enw40/finesso.html.
Canon Kabushiki Kaisha
Fitzpatrick ,Cella, Harper & Scinto
Hudspeth David
Jackson Jakieda
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