Optimal spoken dialog control in hands-free medical information systems

• Autorzy: Sas J.
• Języki publikacji: EN

Abstrakty

EN

In the paper a method of optimal selection of utterances used as command entry-words for voice controlled application is presented. Voice controlled programs seem to be particularly useful in the area of medical informatics, where a physician interacts with a program by voice while operating the medical device or being involved in examinations requiring manual activities. The proposed method selects command words from sets of proposals defined for each command so as to minimize the overall probability of incorrect command recognition. First the entry-word dissimilarity matrix is calculated. The word dissimilarities are evaluated using HMM models consisting of appropriately trained acoustic models of the phonemes constituting words. The trained HMM is used as the sample utterance generator for the word. The artificially created utterance samples are then recognized by speech recognizers created for pairs of words. The estimation of correct recognition probability is used as the word dissimilarity measure. The word dissimilarities are then used to determine the average assessment of words selections that can be used as commands. Selection is created by choosing single word from sets of candidates defined for each command. Finally, suboptimal selection is found by using genetic algorithm. Experiments carried out prove that suboptimal selection of command entry-words can observably increase the accuracy of spoken commands recognition in many cases.

Słowa kluczowe

EN

automatic speech recognition; genetic optimization; medical information systems

PL

rozpoznawanie mowy automatyczne; optymalizacja genetyczna; systemy informacji medycznej

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2009
• Tom: Vol. 13
• Strony: 113--120
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Sas J.

• Institute of Informatics, Wroclaw University of Technology, 50-370 Wroclaw, ul.Wyb. Wyspianskiego 27

Bibliografia

• [1] JELINEK F., Statistical Methods for Speech Recognition, MIT Press, Cambridge, Massachusetts, 1997.
• [2] LYNGSO, R.B. PEDERSEN C., NIELSEN H., Metrics and Similarity Measures for Hidden Markov Models, Proc. of the 7th Int. Conf. on Intelligent Systems for Molecular Biology (ISMB), pp. 178-186, AAAI Press USA, 1999.
• [3] JURAFSKY D., MARTIN J., Speech and Language Processing. An Introduction tp Natural Language Processing, Computational Linguistics and Speech Recognition, Prentice Hall, New Jersey, 2000.
• [4] LI, W.; KUBICHEK, R.F., Output-based Objective Speech Quality Measurement Using Continuous Hidden Markov Models, Signal Processing and Its Applications, 2003. Proc. of Seventh Int. Symposium on, Signal Processing and Its Applications, pp. 389 - 392, 2003.
• [5] YOUNG S., EVERMAN G., The HTK Book, Cambridge University Engineering Department, 2005
• [6] MACKAY W., KONDRAK G., Computing Word Similarity and Identifying Cognates, with Pair Hidden Markov Models Proc. Of the 9th Conference on Computational Natural Language Learning (CoNLL), pp. 40–47, 2005.
• [7] KACALAK W, MAJEWSKI W., Automatic Recognition of Voice Commands in Natural Language Given by the Operator of the Technological Device Using Artificial Neural Network, In: Kurzynski M., Puchala E., Wozniak M., Zolnierek A., Proc. of 4th Int. Conf. on Computer Recognition Systems, CORES, 05, pp. 689-696, Springer Verlag, 2005.
• [8] MOHANTY B., HERSHEY J., OLSEN P., KOZAT S., GOEL V., Optimizing Speech Recognition Grammars Using a Measure of Similarity Between Hidden Markov Models, Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing, pp. 4953 - 4956, 2008.
• [9] PORWIK P., Isolated Word Descriptors and Control Parameters of the Computer Applications. Journal of Medical Informatics & technologies, Vol 10, pp. 35-46, 2006
• [10] PORWIK P., PROKSA R., Word Extraction Method in Human Speech Processing, Journal of Medical Informatics & technologies, Vol 12, pp. 209-216, 2008