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- W2378475641 abstract "In order to better realize speech recognition in complicated noise environment, a new Hidden Markov Model (HMM) was proposed. The relationship between weight coefficient of product HMM and instantaneous Signal Noise Ratio (SNR) was researched and confirmed. In this proposed model, a two-dimension training model was built based on independently trained audio-HMMand visual-HMM, and re-estimation strategy was used to obtain higher recognition accuracy. Generalized Probabilistic Descent (GPD) algorithm was introduced to adjust weight coefficient. The experimental results show that, the proposed bimodal recognition approach with adjusting weight coefficient exhibits good performance on speech recognition in noisy environment." @default.
- W2378475641 created "2016-06-24" @default.
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- W2378475641 date "2009-01-01" @default.
- W2378475641 modified "2023-09-23" @default.
- W2378475641 title "Research of relationship between weight coefficient of product HMM and instantaneous SNR in bimodal speech recognition" @default.
- W2378475641 hasPublicationYear "2009" @default.
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