Presentation | 2005/12/15 Model-Based Wiener Filter for Noise Robust Speech Recognition Takayuki ARAKAWA, Masanori TSUJIKAWA, Ryosuke ISOTANI, |
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Abstract(in English) | We propose a new approach for noise robust speech recognition, Model-Based Wiener Filter. This method takes three steps to estimate clean speech signals from noisy speech signals. The first step is the spectral subtraction (SS). Since the SS averagely subtracts noise components, the estimated speech signals often include distortion. In the second step, the distortion caused by SS is reduced using the minimum mean square error estimation for a Gaussian mixture model. In the final step, the Wiener Filtering is performed with the decision-directed method. Experiments are conducted using the AURORA2-J database. The results show that the proposed method performs as well as the ETSI advanced front-end in average and the variation range of the recognition accuracy according to the kind of noise is about one third, which demonstrates the robustness of the proposed method. |
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Paper # | NLC2005-84,SP2005-117 |
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Committee | NLC |
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Conference Date | 2005/12/15(1days) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Model-Based Wiener Filter for Noise Robust Speech Recognition |
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1st Author's Name | Takayuki ARAKAWA |
1st Author's Affiliation | NEC Media and Information Research Laboratories() |
2nd Author's Name | Masanori TSUJIKAWA |
2nd Author's Affiliation | NEC Media and Information Research Laboratories |
3rd Author's Name | Ryosuke ISOTANI |
3rd Author's Affiliation | NEC Media and Information Research Laboratories |
Date | 2005/12/15 |
Paper # | NLC2005-84,SP2005-117 |
Volume (vol) | vol.105 |
Number (no) | 494 |
Page | pp.pp.- |
#Pages | 2 |
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