• The Journal of the Acoustical Society of Korea
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• v.11 no.1
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• pp.35-41
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• 1992

A speaker identification scheme using the speaker-based VQ codecook of a sustained vowel is proposed and tested. With the pitch synchronous LPC vector of the sustained vowel /i/ as a feature vector, a VQ codebook size of 4 was found to be suitable to characterize each speaker's feature space. For 40 normal speakers (20 males, 20 females), we achieved the correct identification rate of 99.4% with a training data set, and 89.4% with a test data set with speech samples of only 50 pitch periods.

• Proceedings of the KSPS conference
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• 2006.05a
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• pp.77-81
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• 2006

This paper presents a technique of imposing the prosodic features of a native speaker's utterance onto the same sentence uttered by a non-native speaker. Three acoustic aspects of the prosodic features were considered: the fundamental frequency (F0) contour, segmental durations, and the intensity contour. The fundamental frequency contour and the segmental durations of the native speaker's utterance were imposed on the non-native speaker's utterance by using the PSOLA (pitch-synchronous overlap and add) algorithm [1] implemented in Praat[2]. The intensity contour transfer was also done in Praat. The technique of transferring one or more of these prosodic features was elaborated and its implications in the area of language education were discussed.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.592-594
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• 2001

본 연구에서는 음성인식에 있어서 음향모델의 고정도화를 위해 통계적 방법인 HMM과 시간동기형 Viterbi 알고리즘을 기반으로 한 세그멘트되지 않은 음성의 자동 세그멘테이션에 관한 연구를 수행하였다. 본 연구에서는 소량의 세그멘트된 음성에 대해 연속분포형 HMM 기본모델을 작성한 후 이를 표준패턴으로 사용하고, 세그멘트되지 않은 입력음성의 특징 피라미터에 대해 시간동기형 Viterbi 알고리즘의 프레임마다 최대가 되는 지점을 최적경계로 설정하고, 앞에서 구현 최적 경계 정보와 언어학적 지식인 발음사전 정보를 이용하여 음성을 세그멘테이션 하는 것이다. 본 연구와의 비교를 위해 HTK를 이용하여 위와 동일한 과정을 수행하였다. 이렇게 구한 음성의 세그멘테이션 정보를 이용하여 연속분포형 HMM 기본모델과 HTK의 CHMM 기본모델을 각각 작성한 후, 국어공학센터(KLE) 단어 데이터에 대해 단어인식 성능을 평가하였다. 실험결과, KLE 452 남성과 여성에 대해, 본 연구실 인식 시스템은 화자독립 단어인식률 89.4%, 85.1%, HTK의 화자독립 단어인식률 85.1%, 81.9%를 각각 얻었다.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.15-23
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• 2001

This paper presents a voice conversion technique that modifies the utterance of a source speaker as if it were spoken by a target speaker. Feature parameter conversion methods to perform the transformation of vocal tract and prosodic characteristics between the source and target speakers are described. The transformation of vocal tract characteristics is achieved by modifying the LPC cepstral coefficients using Linear Multivariate Regression (LMR). Prosodic transformation is done by changing the average pitch period between speakers, and it is applied to the residual signal using the LP-PSOLA scheme. Experimental results show that transformed speech by LMR and LP-PSOLA synthesis method contains much characteristics of the target speaker.