Journal
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
Volume 19, Issue 3, Pages 600-613Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TASL.2010.2052803
Keywords
Acoustic signal detection; speech analysis
Categories
Funding
- National Science Foundation (NSF)
- US Army
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [911009] Funding Source: National Science Foundation
Ask authors/readers for more resources
We propose a novel long-term signal variability (LTSV) measure, which describes the degree of nonstationarity of the signal. We analyze the LTSV measure both analytically and empirically for speech and various stationary and nonstationary noises. Based on the analysis, we find that the LTSV measure can be used to discriminate noise from noisy speech signal and, hence, can be used as a potential feature for voice activity detection (VAD). We describe an LTSV-based VAD scheme and evaluate its performance under eleven types of noises and five types of signal-to-noise ratio (SNR) conditions. Comparison with standard VAD schemes demonstrates that the accuracy of the LTSV-based VAD scheme averaged over all noises and all SNRs is similar to 6% (absolute) better than that obtained by the best among the considered VAD schemes, namely AMR-VAD2. We also find that, at -10 dB SNR, the accuracies of VAD obtained by the proposed LTSV-based scheme and the best considered VAD scheme are 88.49% and 79.30%, respectively. This improvement in the VAD accuracy indicates the robustness of the LTSV feature for VAD at low SNR condition for most of the noises considered.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available