This paper addresses the problem of voice activity detection (VAD) in noisy environments. The VAD method proposed in this paper is based on a statistical model approach, and estimates statistical models sequentially without a priori knowledge of noise. Namely, the proposed method constructs a clean speech / silence state transition model beforehand, and sequentially adapts the model to the noisy environment by using a switching Kalman filter when a signal is observed. The evaluation is carried out by using a VAD evaluation framework, CENSREC-1-C. The evaluation results revealed that the proposed method significantly outperforms the baseline results of CENSREC-1-C as regards VAD accuracy in real environments.
Bibliographic reference. Fujimoto, Masakiyo / Ishizuka, Kentaro (2007): "Noise robust voice activity detection based on switching kalman filter", In INTERSPEECH-2007, 2933-2936.