• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.894-897
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• 1987

Listener echos, which arise in multiple 4-wire loop connections(MLC) during the evolving switched telephone network, impare voice-band data signal transmission performance. This paper first shows the calculation method of the total number of listener echo loops over N 4-wire physical loops and presents the additative law for listener echos. It next demonstrates that about 4 dB should be ensured to Eke the transmission loss of intraoffice call path be minimum for the voice-band data service in a digital local switch.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.864-868
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• 1987

In this paper we have Investigated the effects of two wideband FDM-FM signals on n-ary QAM signal allocated between FDM-FM signals (in DIV case). Here, we assumed that the instantaneous frequency distribution of wideband FDM-FM signal is Gaussian. The numerical results of symbol error rate are given in graphs as the parameters of carrier to noise ratio (CNR), carrier to interference ratio (CIR) and normalized carrier separation between QAM and FDM-FM carrier frequencies.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1207-1208
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• 2008

We analyzed the performance of hierarchical cellular system with multi traffic(voice traffic, data traffic). We executed the computer simulation by the number of reserved channel for handover. For new call, the more the number of channel reserved, the higher the block probability of call became. The blocking probability of data traffic was higher, compared with that of voice traffic

• Journal of Industrial Technology
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• v.29 no.A
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• pp.95-100
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• 2009

In this paper, we implemented a speaker-independent speech recognizer using the TMS320F28335 DSP which is optimized for control applications. For this implementation, we used a small-sized commercial DSP module and developed a peripheral board including a codec, signal conditioning circuits and I/O interfaces. The speech signal digitized by the TLV320AIC23 codec is analyzed based on MFCC feature extraction methed and recognized using the continuous-density HMM. Thanks to the internal SRAM and flash memory on the TMS320F28335 DSP, we did not need any external memory devices. The internal flash memory contains ADPCM data for voice response as well as HMM data. Since the TMS320F28335 DSP is optimized for control applications, the recognizer may play a good role in the voice-activated control areas in aspect that it can integrate speech recognition capability and inherent control functions into the single DSP.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.122-127
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• 1998

In this paper, we focus on the information retrieval of human individuals who are recorded on the video database. Our purpose is to index persons by their faces or voice and to retrieve their existing time sections on the video data. The database system can track as well as extract a face or voice of a certain person and construct a model of the individual person in self-organization mode. If he appears again at different time, the system can put the mark of the same person to the associated frames. In this way, the same person can be retrieved even if the system does not know his exact name. As the face and speaker modeling, a subspace method is employed to improve the indexing accuracy.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.64-67
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• 1986

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.371-372
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• 1999

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1985.10a
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• pp.99-102
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• 1985

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.04a
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• pp.74-77
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• 1986

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.819-828
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• 2014

In this paper, we analyze the characteristics of the English vocalization of deaf students and present the basic data for the development of personalized English learning aid tools that reflect its features. We visited hearing special schools in Seoul and Daegu and recorded English vocalization of the deaf students in order to analyze the characteristics of deaf students' English vocalization. We analyzed the data by Praat program, an professional voice analysis program. The voice features of deaf students' English vocalization were extracted and then compared with those of non-deaf students' English vocalization.