Abstract
This paper proposes a speech enhancement scheme that leads to significant improvements in recognition performance when used in the Automatic Speech Recognition (ASR) front-end. The proposed approach is based upon adaptive comb filtering. While adaptive comb filtering reduces noise components remarkably, it is rarely effective in reducing non-stationary noises due to its uniformly distributed frequency response. This paper proposes an advanced comb filtering technique that adjusts its spectral magnitude to the original speech, based on the gain modification function, an Minimum Mean Squared Error (MMSE) estimator.
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Acknowledgments
This work was supported by the NAP (National Agenda Project) of the Korea Research Council of Fundamental Science and Technology.
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Park, JS. (2014). Advanced Comb Filtering for Robust Speech Recognition. In: Huang, YM., Chao, HC., Deng, DJ., Park, J. (eds) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Lecture Notes in Electrical Engineering, vol 260. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7262-5_4
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DOI: https://doi.org/10.1007/978-94-007-7262-5_4
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