Speech enhancement of spectral magnitude bin trajectories using Gaussian mixture-model based minimum mean-square error estimators

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Author(s)
O'Connell, James
Paliwal, Kuldip
Wojcicki, Kamil
Year published
2012
Metadata
Show full item recordAbstract
Gaussian mixture-model based minimum mean-square error estimators have been applied to speech enhancement in the temporal, transform (e.g., discrete cosine transform), and subspace domains. In this paper, we propose a method for applying a GMM-based MMSE estimator to spectral magnitude-bin trajectories. In addition, methods for incorporating speech presence uncertainty into the proposed system to improve performance are discussed. The proposed system outperforms previously published GMM-based estimators, and the well-known Ephraim and Malah estimator for 8 kHz telephone-quality speech.Gaussian mixture-model based minimum mean-square error estimators have been applied to speech enhancement in the temporal, transform (e.g., discrete cosine transform), and subspace domains. In this paper, we propose a method for applying a GMM-based MMSE estimator to spectral magnitude-bin trajectories. In addition, methods for incorporating speech presence uncertainty into the proposed system to improve performance are discussed. The proposed system outperforms previously published GMM-based estimators, and the well-known Ephraim and Malah estimator for 8 kHz telephone-quality speech.
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Conference Title
Proceedings of the 14th Australasian International Conference on Speech Science and Technology
Volume
54
Issue
2
Copyright Statement
© 2012 ASSTA. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
Subject
Signal Processing