In this work, a novel voice activity detection (VAD) algorithm that uses speech absence probability (SAP) based on Teager energy (TE) was proposed for speech enhancement. The proposed method employs local SAP (LSAP) b...In this work, a novel voice activity detection (VAD) algorithm that uses speech absence probability (SAP) based on Teager energy (TE) was proposed for speech enhancement. The proposed method employs local SAP (LSAP) based on the TE of noisy speech as a feature parameter for voice activity detection (VAD) in each frequency subband, rather than conventional LSAP. Results show that the TE operator can enhance the ability to discriminate speech and noise and further suppress noise components. Therefore, TE-based LSAP provides a better representation of LSAP, resulting in improved VAD for estimating noise power in a speech enhancement algorithm. In addition, the presented method utilizes TE-based global SAP (GSAP) derived in each frame as the weighting parameter for modifying the adopted TE operator and improving its performance. The proposed algorithm was evaluated by objective and subjective quality tests under various environments, and was shown to produce better results than the conventional method.展开更多
基金Project supported by Inha University Research GrantProject(10031764) supported by the Strategic Technology Development Program of Ministry of Knowledge Economy, Korea
文摘In this work, a novel voice activity detection (VAD) algorithm that uses speech absence probability (SAP) based on Teager energy (TE) was proposed for speech enhancement. The proposed method employs local SAP (LSAP) based on the TE of noisy speech as a feature parameter for voice activity detection (VAD) in each frequency subband, rather than conventional LSAP. Results show that the TE operator can enhance the ability to discriminate speech and noise and further suppress noise components. Therefore, TE-based LSAP provides a better representation of LSAP, resulting in improved VAD for estimating noise power in a speech enhancement algorithm. In addition, the presented method utilizes TE-based global SAP (GSAP) derived in each frame as the weighting parameter for modifying the adopted TE operator and improving its performance. The proposed algorithm was evaluated by objective and subjective quality tests under various environments, and was shown to produce better results than the conventional method.
