• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.57-61
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• 1984

In this study, the system is proposed which can be used for recognition of Koean single vowles "ㅏ, ㅓ, ㅗ, ㅜ, ㅡ, ㅣ, ㅐ, ㅔ, ㅚ,", and automatic recognition is processed using $\mu$-computer. 3 men of not-being-studied are participated in this experiment. Using the period of vowels, one part of the steady state is selected for high speed recognition, and amplitude comparison method, LPC, PARCOR, and Formant are used for parameter of recognition. Formant is obtained by peak picking method using LPC, and then vowels are recognized by amplitude comparison method, LPC, PARCOR, and Formant. As a result, Recognition rates are 90.1% for amplitude comparison method, 93.1% for LPC, 100% for PARCOR, 88.8% for using formant.

• Journal of the Korea Computer Industry Society
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• v.2 no.4
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• pp.471-480
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• 2001

In this thesis, we perform the experiment of speaker recognition by identifying vowels in the pronunciation of each speaker using Adaptive Resource Theory 2(ART2) model. The 5 adult males and 5 adult females pronounce from 0 to 9 digits. We extract the vowels from the pronunciation of each speaker first, we are extracted characteristic coefficient through a pitch detection algorithm, a LPC analysis, and a LPC cepstral analysis to generate an input pattern of ART2. The experimental results showed that pitch coefficients are somewhat more enhanced than LPC or LPC cepstral coefficient.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.96-102
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• 1995

This paper presents the VHSIC Hardware Description Language(VHDL) implementation of the Fixed Point Covariance Lattice(FLAT) algorithm for an Linear Predictive Coding(LPC) analysis and its related algorithms, such as the forth order high pass Infinite Impulse Response(IIR) filter, covariance matrix calculation, and Spectral Smoothing Technique(SST) in the Vector Sum Exited Linear Predictive(VSELP) speech coder that has been Selected as the standard speech coder for the North America and Japanese digital cellular. Existing Digital Signal Processor(DSP) chips used in digital cellular phones are derived from general purpose DSP chips, and thus, these DSP chips may not be optimal and effective architectures are to be designed for the above mentioned algorithms. Then we implemented the VHDL code based on the C code, Finally, we verified that VHDL results are the same as C code results for real speech data. The implemented VHDL code can be used for performing logic synthesis and for designing an LPC Application Specific Integrated Circuit(ASOC) chip and DsP chips. We first developed the C language code to investigate the correctness of algorithms and to compare C code results with VHDL code results block by block.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.679-682
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• 1999

This paper proposes the LSF or LSP that is the method of using to transfer the speech parameters after processed the speech to LPC, which is digital coding transferring efficiently, for the best quality and the lowest bit rate of parameters. The new revised transform algorithm between LSF and LPC coefficients is proposed. The proposed algorithm eliminates all multiplications, computes fewer operations, and reduces memory buffer sizes.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.554-559
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• 2003

In this paper the possibility of snorer-dependent snore recognition using cepstral coefficients was suggested. We assumed that snore and speech sounds have some similarities and we used cepstral coefficients which are widely used for speech recognition. Snoring data were acquired from 18 persons including 5 patients diagnosed as snore patient. To evaluate the performance of proposed method, the distance ratio based on LPC cepstral coefficients was selected as an index for snorer-dependent snore recognition. As a result, distance ratio of 3 was selected as optimal value showing the most efficient snorer-dependent snore recognition, which is high accuracy of 95.05％ on average. In conclusion, the proposed method showed the possibilities to be applied in clinical applications for snorer-dependent snore recognition.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.5
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• pp.1-6
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• 1978

This paper is a sequel of the previous paperl) on speech digitization and bandwidth compression techniques. Several recently developed vocoding techniques, that is, linear predictive coding (LPC), formant vocoding, residual excited linear prediction (RELP) vocoding, and adaptive predictive coding(APC) are discussed. Throughout the leaper emphasis is placed on the LPC approach that is presently the most promising technique in speech compression. In addition, current problems and possible solutions are discussed.

• Korean Journal of Food Science and Technology
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• v.18 no.5
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• pp.398-405
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• 1986

The food quality of lupin seed, i.e. soaking, cooking, sprout growing and mold growing for fermentation, was investigated by using the seed of Lupinus angustifolius harvested in Western Australia. A method to produce lupin seed protein concentrate (LPC) was developed, and the wage of LPC in Korean food system was investigated. The water soaking rate of lupin seed was faster than that of soybean, but the cooking rate of lupin seed was much slower compared to soybean. The thermal softening time, $D_{100}$, was 345 min for lupin seed and 84 min for soybean. A two-phase solvent extraction system consisting of haxane-alcohol-water could effectively remove the residual bitter taste, lipid and yellow pigments of lupin seed flour, and the resulting LPC contained over 50% protein and had bland flavor and milky white color. Treatment of LPC with carbohydrate decomposing enzymes resulted in a product of more soluble and higher concentration of protein. Methods to produce lupin seed vegetable milk and lactic beverages from LPC products were discussed.

• The Korean Journal of Physiology and Pharmacology
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• v.6 no.2
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• pp.93-99
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• 2002

Effects of oxidized low-density lipoprotein (ox-LDL), $1-{\alpha}-stearoyl-lysophosphatidylcholine$ (LPC), on intracellular $Ca^{2+}$ concentration were examined in mouse endothelial cells by measuring intracellular $Ca^{2+}$ concentration $([Ca^{2+}]_i)$ with fura 2-AM and reverse transcription-polymerase chain reaction (RT-PCR). LPC increased $[Ca^{2+}]_i$ under the condition of 1.5 mM $[Ca^{2+}]_o$ but did not show any effect under the nominally $Ca^{2+}-free$ condition. Even after the store depletion with $30{\mu}M$ 2,5-di-tert- butylhydroquinone (BHQ) or $30{\mu}M$ ATP, LPC could still increase the $[Ca^{2+}]_i$ under the condition of 1.5 mM $[Ca^{2+}]_o.$ The time required to increase [$Ca{2+}$]i (about 1 minute) was longer than that for ATP-induced $[Ca^{2+}]_i$ increase $(10{\sim}30\;seconds).$ LPC-induced $[Ca^{2+}]_i$ increase was completely blocked by $1{\mu}M\;La^{3+}.$ Transient receptor potential channel(trpc) 4 mRNA was detected with RT-PCR. From these results, we suggest that LPC increased $[Ca^{2+}]_i$ via the increase of $Ca^{2+}$ influx through the $Ca^{2+}$ routes which exist in the plasma membrane.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.146-156
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• 1989

This paper discusses how to choose speech parameters and decision logics to improve the performance of speaker recognition systems. It also considers the influence of the reference patterns on the speaker recognition. It is observed from the performance analysis based on LPSs, PARCOR coefficients and LPC-cepstrum coefficients that LPC-cepstrum coefficients are superior to the others in speaker recognition without regard to the reference patterns. In order to improve the recognition performance, a new decision logic is proposed based on a generalized-distance concept. It differs from the existing methods in that it considers the statistics of customer and impostors at the same time. It turns out from a speaker verification test that the proposed decision logic ferforms better than the existing ones.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.96-107
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• 1996

A voice personality transformation algorithm using orthogonal vector space conversion is proposed in this paper. Voice personality transformation is the process of changing one person's acoustic features (source) to those of another person (target). In this paper, personality transformation is achieved by changing the LPC cepstrum coefficients, excitation spectrum and pitch contour. An orthogonal vector space conversion technique is proposed to transform the LPC cepstrum coefficients. The LPC cepstrum transformation is implemented by principle component decomposition by applying the Karhunen-Loeve transformation and minimum mean-square error coordinate transformation(MSECT). Additionally, we propose a pitch contour modification method to transform the prosodic characteristics of any speaker. To do this, reference pitch patterns for source and target speaker are firstly built up, and speaker's one. The experimental results show the effectiveness of the proposed algorithm in both subjective and objective evaluations.