15th Annual Conference of the International Speech Communication Association

September 14-18, 2014

Binary Mask Estimation Based on Frequency Modulations

Chung-Chien Hsu, Jen-Tzung Chien, Tai-Shih Chi

National Chiao Tung University, Taiwan

In this paper, a binary mask estimation algorithm is proposed based on modulations of speech. A multi-resolution spectro-temporal analytical auditory model is utilized to extract modulation features to estimate the binary mask, which is often used in speech segregation applications. The proposed method estimates noise from the beginning of each test sentence, a common approach seen in many conventional speech enhancement algorithms, to further enhance the modulation features. Experimental results demonstrate that the proposed method outperforms the AMS-GMM system in terms of the HIT-FA rate when estimating the binary mask.

Full Paper

Bibliographic reference.  Hsu, Chung-Chien / Chien, Jen-Tzung / Chi, Tai-Shih (2014): "Binary mask estimation based on frequency modulations", In INTERSPEECH-2014, 993-997.