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Original scientific paper
https://doi.org/10.2498/cit.1001284

Applying the Generalized Dombi Operator Family to the Speech Recognition Task

Gábor Gosztolya
József Dombi
András Kocsor

Fulltext: english, pdf (466 KB) pages 285-293 downloads: 398* cite
APA 6th Edition
Gosztolya, G., Dombi, J. & Kocsor, A. (2009). Applying the Generalized Dombi Operator Family to the Speech Recognition Task. Journal of computing and information technology, 17 (3), 285-293. https://doi.org/10.2498/cit.1001284
MLA 8th Edition
Gosztolya, Gábor, et al. "Applying the Generalized Dombi Operator Family to the Speech Recognition Task." Journal of computing and information technology, vol. 17, no. 3, 2009, pp. 285-293. https://doi.org/10.2498/cit.1001284. Accessed 21 Apr. 2021.
Chicago 17th Edition
Gosztolya, Gábor, József Dombi and András Kocsor. "Applying the Generalized Dombi Operator Family to the Speech Recognition Task." Journal of computing and information technology 17, no. 3 (2009): 285-293. https://doi.org/10.2498/cit.1001284
Harvard
Gosztolya, G., Dombi, J., and Kocsor, A. (2009). 'Applying the Generalized Dombi Operator Family to the Speech Recognition Task', Journal of computing and information technology, 17(3), pp. 285-293. https://doi.org/10.2498/cit.1001284
Vancouver
Gosztolya G, Dombi J, Kocsor A. Applying the Generalized Dombi Operator Family to the Speech Recognition Task. Journal of computing and information technology [Internet]. 2009 [cited 2021 April 21];17(3):285-293. https://doi.org/10.2498/cit.1001284
IEEE
G. Gosztolya, J. Dombi and A. Kocsor, "Applying the Generalized Dombi Operator Family to the Speech Recognition Task", Journal of computing and information technology, vol.17, no. 3, pp. 285-293, 2009. [Online]. https://doi.org/10.2498/cit.1001284

Abstracts
In the automatic speech recognition (ASR) problem, the task of constructing one word- or sentence-level probability from the
available phoneme-level probabilities is a very important one. Here we try to improve the performance of ASR systems by applying
operators taken from fuzzy logic which have the sort of properties this problem requires. In this paper we do this by using the Generalized Dombi Operator, which, by its two adjustable parameters and incorporating other well-known fuzzy operators, seems quite suitable. To properly adjust these parameters, we used the public optimization package called Snobfit. The results show
that our approach is surprisingly successful: we were able to reduce the overall error rate by 53.4%.

Hrčak ID: 44866

URI
https://hrcak.srce.hr/44866

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