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Robust voice activity detection algorithm for estimating noise spectrum

Robust voice activity detection algorithm for estimating noise spectrum

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A new voice activity detection(VAD) algorithm is proposed for estimating the spectrum of car noise in which noise is filtered out in the frequency domain. The proposed algorithm uses the log energy parameters which are composed of two parts in the critical band. The algorithm detects the noise period by applying two adaptive thresholds to each part. Using the noise period we can reliably estimate the time-varying noise characteristics. The advantage of the proposed technique is that it can prevent incorrect detections caused by unvoiced or nasal sounds with high frequency components being covered by car noise with low frequency components. The algorithm is suitable for real time implementation with one microphone. Also, a speaker-independent speech recognition system has been implemented for car navigation using a fixed point Oak DSP system, which incorporates the proposed VAD algorithm. The system enhanced the recognition rates for 12 isolated command words to 94.52% compared with the 80.7% of the baseline recogniser.

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