지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
In this paper, we introduce the automatic speaker identification system ‘SPO(Supreme Prosecutors Office) Verifier’. SPO Verifier is a GMM(Gaussian mixture model)-UBM(universal background model) based automatic speaker recognition system and has been developed using Korean speakers’ utterances. This system uses a channel compensation algorithm to compensate recording device characteristics. The system can give the users the ability to manage reference models with utterances from various environments to get more accurate recognition results. To evaluate the performance of SPO Verifier on Korean speakers, we compared this system with one of the most widely used commercial systems in the forensic field. The results showed that SPO Verifier shows lower EER(equal error rate) than that of the commercial system.
목차
ABSTRACT
1. 서론
2. SPO Verifier 자동화자식별 기술
3. 시스템의 설계 및 구현
4. 성능 평가 실험
5. 결론
참고문헌
참고문헌 (10)
참고문헌 신청
1. [단행본] - Huang, X. / 2001 / Spoken languageprocessing : a guide to theory algorithm, and systemdevelopment / Prentice Hall PTR
2. [학술지(정기간행물)] - Atal, B. S / 1974 / Effectiveness of linear predictioncharacteristics of the speech wave for automatic speakeridentification and verification / Journal of the Acoustical Societyof America 55 (6) : 1304 ~ 1312
3. [학술지(정기간행물)] - Viikki, O. / 1998 / Cepstral domain segmentalfeature vector normalization for noise robust speechrecognition / Speech Communication 25 : 133 ~ 147
4. [인터넷자원] - Smith, L. I. / / A tutorial on principal componentsanalysis
5. [학술지(정기간행물)] - Reynolds, D. A. / 1995 / Robusttext-independent speaker identification using Gaussian mixturespeaker models / IEEE Trans. Speech Audio Processing 3 : 72 ~ 83
2. [학술지(정기간행물)] - Atal, B. S / 1974 / Effectiveness of linear predictioncharacteristics of the speech wave for automatic speakeridentification and verification / Journal of the Acoustical Societyof America 55 (6) : 1304 ~ 1312
3. [학술지(정기간행물)] - Viikki, O. / 1998 / Cepstral domain segmentalfeature vector normalization for noise robust speechrecognition / Speech Communication 25 : 133 ~ 147
4. [인터넷자원] - Smith, L. I. / / A tutorial on principal componentsanalysis
5. [학술지(정기간행물)] - Reynolds, D. A. / 1995 / Robusttext-independent speaker identification using Gaussian mixturespeaker models / IEEE Trans. Speech Audio Processing 3 : 72 ~ 83
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UCI(KEPA) : I410-ECN-0101-2014-701-001338071