Robust Speech Recognition Using a Cepstral Minimum-Mean-Square-Error-Motivated Noise Suppressor

By Dong Yu, Li Deng, Jasha Droppo, Jian Wu, Yifan Gong, A. Acero. 2008

70 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. S. Renals
2. Arnab Ghoshal
3. Liang Lu
4. Kean K. Chin
5. Jinyu Li
6. Dong Yu
7. Li Deng
8. Shinji Watanabe

In Signal Processing

1. S. Renals
2. Arnab Ghoshal
3. Liang Lu
4. Kean K. Chin
5. Jinyu Li
6. Dong Yu
7. Li Deng
8. Shinji Watanabe

Citations in the corpus

• Joint Uncertainty Decoding for Noise Robust Subspace Gaussian Mixture Models (2013, methodology): “Many feature domain approaches have been proposed including spectral subtraction, cepstral mean and variance normalization (CMN/CVN), cepstral maximum mean square error estimation [2], SPLICE [3], ALGONQUIN [4] and feature space vector Taylor series (VTS) compensation [5].”