The Self-adaptive Voice Activity Detection Algorithm based on timefrequency Parameters
نویسندگان
چکیده
منابع مشابه
The Self-adaptive Voice Activity Detection Algorithm based on time- frequency Parameters
In order to solve the inferior performance and sad self-adaptive of the traditional voice activity detection algorithm in an environment with low Signal to Noise Ratio (SNR), a new self-adaptive voice activity detection algorithm based on time-frequency (TF) parameters is put forward. After introducing the time-domain log-energy and improved mel-scale log-energy, the new TF parameters are acqui...
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Voice Activity Detection (VAD) is a crucial step for speech processing, which detecting accuracy and speed directly affects the effect of subsequent processing. Some voice processing system based phone or in the indoor environment, which need simple and quick method of VAD, for these representative voice signal, this paper proposes a new algorithm which is adaptive and quick based on a major im...
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Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...
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A new voice activity detection algorithm based on long-term pitch divergence is presented. The long-term pitch divergence not only decomposes speech signals with a bionic decomposition but also makes full use of long-term information. It is more discriminative comparing with other feature sets, such as long-term spectral divergence. Experimental results show that among six analyzed algorithms, ...
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Voice activity detection (VAD) in real-world noise is a very challenging task. In this paper, a two-step methodology is proposed to solve the problem. First, segments with non-stationary components, including speech and dynamic noise, are located using sub-band energy sequence analysis (SESA). Secondly, voice is detected within the selected segments employing the proposed method concerning its ...
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ژورنال
عنوان ژورنال: The Open Automation and Control Systems Journal
سال: 2014
ISSN: 1874-4443
DOI: 10.2174/1874444301406011661