International audienceStatistical likelihood ratio test is a widely used voice activity detection (VAD) method, in which the likelihood ratio of the current temporal frame is compared with a threshold. A fixed threshold is always used, but this is not suitable for various types of noise. In this paper, an adaptive threshold is proposed as a function of the local statistics of the likelihood ratio. This threshold represents the upper bound of the likelihood ratio for the non-speech frames, whereas it remains generally lower than the likelihood ratio for the speech frames. As a result, a high non-speech hit rate can be achieved, while maintaining speech hit rate as large as possible
The emerging applications of wireless speech communication are demanding increasing levels of perfor...
Abstract—One of the key issues in practical speech processing is to achieve robust voice activity de...
Statistical methods for voice activity detection (VAD) have shown impressive performance especially ...
International audienceStatistical likelihood ratio test is a widely used voice activity detection (V...
Abstract—Currently, there are technology barriers inhibiting speech processing systems that work in ...
Abstract The role of the statistical model-based voice activity detector (SMVAD) is to detect speech...
This paper presents a novel voice activity detector (VAD) for improving speech detection robustness ...
Abstract. A robust and effective voice activity detection (VAD) al-gorithm is proposed for improving...
Traditionally voice activity detection algorithms are based on any combination of general speech pr...
Voice activity detection (VAD) is a fundamental task in various speech-related applications, such as...
In this thesis, we propose a few practical statistical voice activity detectors (VADs) which combine...
Detection of Voice in speech signal is a challenging problem in developing high-performance systems ...
This paper shows a revised statistical test for voice activi-ty detection in noise adverse environme...
This paper proposes a new statistical model-based likelihood ratio test (LRT) VAD to obtain reliable...
Preprint del artículo públicado online el 31 de mayo 2018Voice activity detection (VAD) is an essent...
The emerging applications of wireless speech communication are demanding increasing levels of perfor...
Abstract—One of the key issues in practical speech processing is to achieve robust voice activity de...
Statistical methods for voice activity detection (VAD) have shown impressive performance especially ...
International audienceStatistical likelihood ratio test is a widely used voice activity detection (V...
Abstract—Currently, there are technology barriers inhibiting speech processing systems that work in ...
Abstract The role of the statistical model-based voice activity detector (SMVAD) is to detect speech...
This paper presents a novel voice activity detector (VAD) for improving speech detection robustness ...
Abstract. A robust and effective voice activity detection (VAD) al-gorithm is proposed for improving...
Traditionally voice activity detection algorithms are based on any combination of general speech pr...
Voice activity detection (VAD) is a fundamental task in various speech-related applications, such as...
In this thesis, we propose a few practical statistical voice activity detectors (VADs) which combine...
Detection of Voice in speech signal is a challenging problem in developing high-performance systems ...
This paper shows a revised statistical test for voice activi-ty detection in noise adverse environme...
This paper proposes a new statistical model-based likelihood ratio test (LRT) VAD to obtain reliable...
Preprint del artículo públicado online el 31 de mayo 2018Voice activity detection (VAD) is an essent...
The emerging applications of wireless speech communication are demanding increasing levels of perfor...
Abstract—One of the key issues in practical speech processing is to achieve robust voice activity de...
Statistical methods for voice activity detection (VAD) have shown impressive performance especially ...