Next Article in Journal
Thermodynamic Analysis for Buoyancy-Induced Couple Stress Nanofluid Flow with Constant Heat Flux
Next Article in Special Issue
Maximum Correntropy Criterion Kalman Filter for α-Jerk Tracking Model with Non-Gaussian Noise
Previous Article in Journal
Gravitational Contribution to the Heat Flux in a Simple Dilute Fluid: An Approach Based on General Relativistic Kinetic Theory to First Order in the Gradients
Previous Article in Special Issue
Complexity Analysis of Neonatal EEG Using Multiscale Entropy: Applications in Brain Maturation and Sleep Stage Classification
Open AccessArticle

Real-Time Robust Voice Activity Detection Using the Upper Envelope Weighted Entropy Measure and the Dual-Rate Adaptive Nonlinear Filter

1
Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka 75450, Malaysia
2
Motorola Solutions Malaysia Sdn. Bhd., Plot 2 Technoplex Industrial Park, Mukim 12 SWD, Bayan Lepas, Penang 11900, Malaysia
*
Author to whom correspondence should be addressed.
Entropy 2017, 19(11), 487; https://doi.org/10.3390/e19110487
Received: 19 June 2017 / Revised: 1 September 2017 / Accepted: 8 September 2017 / Published: 28 October 2017
(This article belongs to the Special Issue Entropy in Signal Analysis)
Voice activity detection (VAD) is a vital process in voice communication systems to avoid unnecessary coding and transmission of noise. Most of the existing VAD algorithms continue to suffer high false alarm rates and low sensitivity when the signal-to-noise ratio (SNR) is low, at 0 dB and below. Others are developed to operate in offline mode or are impractical for implementation in actual devices due to high computational complexity. This paper proposes the upper envelope weighted entropy (UEWE) measure as a means to enable high separation of speech and non-speech segments in voice communication. The asymmetric nonlinear filter (ANF) is employed in UEWE to extract the adaptive weight factor that is subsequently used to compensate the noise effect. In addition, this paper also introduces a dual-rate adaptive nonlinear filter (DANF) with high adaptivity to rapid time-varying noise for computation of the decision threshold. Performance comparison with standard and recent VADs shows that the proposed algorithm is superior especially in real-time practical applications. View Full-Text
Keywords: voice activity detector (VAD); gammatone filter; asymmetric nonlinear filter; weight factor; entropy; dual-rate adaptive nonlinear filter voice activity detector (VAD); gammatone filter; asymmetric nonlinear filter; weight factor; entropy; dual-rate adaptive nonlinear filter
Show Figures

Figure 1

MDPI and ACS Style

Ong, W.Q.; Tan, A.W.C.; Vengadasalam, V.V.; Tan, C.H.; Ooi, T.H. Real-Time Robust Voice Activity Detection Using the Upper Envelope Weighted Entropy Measure and the Dual-Rate Adaptive Nonlinear Filter. Entropy 2017, 19, 487.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop