• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.167-170
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• 2000

일반적인 한국어 대용량 어휘인식에 사용되는 triphone 모델은 한국어의 특성을 잘 표현한다는 장점이 있으나 인식시간이 길어지게 된다. 이러한 triphone 모델의 단점을 극복하기 위해 음절단위 HMM 모델을 사용하는 방법이 있는데 이 모델은 인식시간을 줄일 수 있으나 triphone 모델에 비해서 인식률이 낮다. 본 논문에서는 음성 인식시간을 단축시키고 조음현상을 고려하기 위하여 초성과 종성 자음은 각각의 biphones으로 나타내고 중성 모음은 1개의 monophone으로 나타내는 모델을 제안하였다. PBW445 음성 데이터베이스에 대한 실험결과, 제안한 인식모델이 triphone 모델에 가까운 인식률을 나타내었으며, 인식시간을 크게 단축하였다.

• Speech Sciences
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• v.9 no.3
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• pp.61-73
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• 2002

We collect the Korean Database which can be trained for the speech recognition engine in an automotive environment. We describe the overall trends of the Korean database collections in this paper and suggest a database collection method for the speech recognition system of the car-kit and explain several conditions in collecting the database in the automotive environments. Finally, we expain an effective method of the Korean database collection in the automobile and the results of the database colletions, and the devised softwares used for the collection of the database.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.69-72
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• 2004

In this paper, we tried to develop a vowel training assistant method using vowel formant statistics. Formant statistics were obtained from PBW set consists of 452 words from 8 persons. Then, we calculated distance from input formants to each center of vowel formant space. Based on the distance, direct ions to correct the speaker's manner of articulation, i .e. position of jaw and tongue.

• Bulletin of the Korean Mathematical Society
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• v.54 no.2
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• pp.463-484
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• 2017

We construct a weak Hopf algebra $wX_q(A_1)$ corresponding to non-standard quantum group $X_q(A_1)$. The PBW basis of $wX_q(A_1)$ is described and all the highest weight modules of $wX_q(A_1)$ are classified. Finally we give the Clebsch-Gordan decomposition of the tensor product of two highest weight modules of $wX_q(A_1)$.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.325-328
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• 2003

In this paper, we tried to develop a vowel training assistant method using vowel formant statistics. Formant statistics were obtained from PBW set consists of 452 words from 8 persons. Then, we calculated distance from input formants to each center of vowel formant space. Based on the distance, directions to correct the speaker's manner of articulation, i.e. position of jaw and tongue.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.663-667
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• 1999

In this paper, we review the conventional speaker verification algorithm and present the text-dependent speaker verification system for application over telephone lines and its result of experiments. We apply blind-segmentation algorithm which segments speech into sub-word unit without linguistic information to the speaker verification system for training speaker model effectively with limited enrollment data. And the World-mode] that is created from PBW DB for score normalization is used. The experiments are presented in implemented system using database, which were constructed to simulate field test, and are shown 3.3% EER.

• Speech Sciences
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• v.11 no.4
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• pp.7-15
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• 2004

In this paper, we develop a vowel training assistant method using vowel formant statistics. Formant statistics were obtained from a PBW set consisting of 452 words from 8 persons. Then we calculated distance from input formants to each center of vowel formant space. Based on the distance, directions could be given to correct the speaker's manner of articulations, i.e. position of jaw and tongue.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.37-40
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• 2000

전화망 음성 인식 시스템에서 사용할 수 있는 데이터베이스 구축의 질과 양은 인식 시스템의 성능에 중대한 영향을 미친다. 따라서, 전화망 음성 데이터 베이스 구축에 관한 효과적인 방법들이 연구되고 있다. 본 논문은 공용으로 사용할 수 있는 음성 데이터 베이스의 전화망 변환 방법 및 활용 방안에 대하여 소개한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.103-111
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• 2004

The method of speaker normalization has been known as the successful method for improving the accuracy of speech recognition at speaker independent speech recognition system. A frequency warping approach is widely used method based on maximum likelihood for speaker normalization. This paper propose a new power spectrum warping approach to making improvement of speaker normalization better than a frequency warping. Th power spectrum warping uses Mel-frequency cepstrum analysis(MFCC) and is a simple mechanism to performing speaker normalization by modifying the power spectrum of Mel filter bank in MFCC. Also, this paper propose the hybrid VTN combined the Power spectrum warping and a frequency warping. Experiment of this paper did a comparative analysis about the recognition performance of the SKKU PBW DB applied each speaker normalization approach on baseline system. The experiment results have shown that a frequency warping is 2.06%, the power spectrum is 3.06%, and hybrid VTN is 4.07% word error rate reduction as of word recognition performance of baseline system.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1
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• pp.48-53
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• 2003

Eigenvoice method is known to be adequate for fast speaker adaptation, but it hardly shows additional improvement with increased amount of adaptation data. In this paper, to deal with this problem, we propose a modified method estimating the weights of eigenvoices in each feature vector dimension. We also propose an adaptation mode selection scheme that one method with higher performance among several adaptation methods is selected according to the amount of adaptation data. We used POW DB to construct the speaker independent model and eigenvoices, and utterances(ranging from 1 to 50) from PBW 452 DB and the remaining 400 utterances were used for adaptation and evaluation, respectively. With the increased amount of adaptation data, proposed dimensional eigenvoice method showed higher performance than both conventional eigenvoice method and MLLR. Up to 26% of word error rate was reduced by the adaptation mode selection between eigenvoice and dimensional eigenvoice methods in comparison with conventional eigenvoice method.