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IEICE Transactions on Information and Systems 2008 E91-D(3):467-477; doi:10.1093/ietisy/e91-d.3.467
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Copyright © 2008 The Institute of Electronics, Information and Communication Engineers

Special Section on Robust Speech Processing in Realistic Environments -- Papers -- Voice Activity Detection

Noise Robust Voice Activity Detection Based on Switching Kalman Filter

Masakiyo FUJIMOTO1 and Kentaro ISHIZUKA1

1 The authors are with NTT Communication Science Laboratories, NTT Corporation, Kyoto-fu, 619–0237 Japan. E-mail: masakiyo{at}cslab.kecl.ntt.co.jp; ishizuka{at}cslab.kecl.ntt.co.jp


  Abstract

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. In this paper, we carried out two evaluations. In the first, we observed that the proposed method significantly outperforms conventional methods as regards voice activity detection accuracy in simulated noise environments. Second, we evaluated the proposed method on 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. In addition, we confirmed that the proposed method helps to improve the accuracy of concatenated speech recognition in real environments.

Key Words: voice activity detection, statistical model, switching Kalman filter, noisy environment, CENSREC-1-C

Manuscript received June 29, 2007. Manuscript revised September 12, 2007.


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