말소리와 음성과학 (Phonetics and Speech Sciences)
- 제3권2호
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- Pages.65-70
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- 2011
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- 2005-8063(pISSN)
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- 2586-5854(eISSN)
잡음 환경 하에서의 입술 정보와 PSO-NCM 최적화를 통한 거절 기능 성능 향상
Improvement of Rejection Performance using the Lip Image and the PSO-NCM Optimization in Noisy Environment
- 투고 : 2011.05.25
- 심사 : 2011.06.23
- 발행 : 2011.06.30
초록
Recently, audio-visual speech recognition (AVSR) has been studied to cope with noise problems in speech recognition. In this paper we propose a novel method of deciding weighting factors for audio-visual information fusion. We adopt the particle swarm optimization (PSO) to weighting factor determination. The AVSR experiments show that PSO-based normalized confidence measures (NCM) improve the rejection performance of mis-recognized words by 33%.
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