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- W2183269614 abstract "This presents a robust voice activity detector (V AD) based on Hidden Markov Models (HMM) in stationary and non-stationary noise environments: inside motor vehicles (like cars or planes) or inside buDdings close to high traffic places (like in a control tower for air tramc control (ATC». In these environments, there is a high stationary noise level caused by vehicle motors and additionally, there could be people speaking at certain distance from the main speaker producing non-stationary noise. The V AD presented herein Is characterized by a new front-end and a noise level adaptation process that increases significantly the V AD robustness for different signal to noise ratios (SNRs). The feature vector used by the V AD includes the most relevant Mel Frequency Cepstral Coefficients (MF CC), normalized log energy, and delta log energy. The proposed V AD has been evaluated and compared to other weD-known V ADs using three databases containing different noise conditions: speech in clean environments (SNRs > 20 dB), speech recorded in stationary noise environments (inside or close to motor vehicles), and finally, speech in non-stationary environments (including noise from bars, television, and far-field speakers). In the three cases, the detection error obtained with the proposed V AD is the lowest for all SNRs compared to Acero's V AD (reference ofthis work" @default.
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- W2183269614 date "2011-01-01" @default.
- W2183269614 modified "2023-09-27" @default.
- W2183269614 title "for Noisy Environments" @default.
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