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Cho Dong-Uk
- The Journal of Korean Institute of Communications and Information Sciences
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- v.31 no.5C
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- pp.548-555
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- 2006
This paper proposes on the Sasang constitution classification method which is the most important things in the Sasang constitution medicine. Pre-existing methods of Sasang constitution classification are a shape of the body and its countenance & morpological aspect and temper. Many diagnostic methods have been developed and used including the questionnaires on personal life style and propensities(QSCC, QSCC II), and the tonal analysis of person's voice. Recently the constitutional acupunture and the herbal medicine response analyses are developed and used additionally. But these methods which is done by the doctor's intuition. In this article, I propose a methodology to classify the Sasang constitution. pitch, intensity and formants are used to classify the Sasang constitution by comparing the similarities and differencies of tonal analysis. Finally, the validity of the method is proven through the experiments.
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Lee, Ki-Yeong;Choi, Kap-Seok
- The Journal of the Acoustical Society of Korea
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- v.11 no.3
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- pp.40-52
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- 1992
In this paper, we propose the speaker adaptive word recognition method using a mapped membership function, in order to absorb a fluctuation owing to personal difference which is a problem of speaker independent speech recognition. In the training procedure of this method, the mapped membership function is made with the fuzzy theory introducded into a mapped codebook, between an unknown speaker's spectrum pattern and a standard speaker's one. In the recognition procedure, an input pattern of an unknown speaker is reconstructed to the pattern which is adapted to that of a standard speaker by the mapped membership function. To show the validity of this method, word recognition experiments are carried out using 28 DDD area names. The recognition rate of the conventional speaker-adaptive method using a mapped codebook by VQ is 64.9[%], and that made by a fuzzy VQ is 76.2[%]. Throughout the experiment using a mapped membership function, we can achieve 95.4[%] recognition rate. This shows that our proposed method is more excellent in recognition performance. Moreover, this method doesn't need an iterative training procedure to make the mapped membership function, and memory capacity and computation requirements for this method are reduced to 1/30 and 1/500 time of those for the conventional method using a mapped codebook, respectively.
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