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A clustering based feature selection method in spectro ...
In this paper, a new clustering based method is proposed for secondary feature selection/extraction in the spectro-temporal domain. In the proposed representation, Gaussian mixture models (GMM) and weighted K-means (WKM) clustering techniques are applied to spectro-temporal domain to reduce the dimensions of the features space. The elements of ......
On-line Gaussian mixture modeling in the log-power domain ...
1. Introduction. The Gaussian mixture model (GMM) has been widely used in many applications of speech processing, including speech recognition, speaker verification and noise adaptation (The HTK Book, 1995, Reynolds and Rose, 1995, Acero, 1993, Burshtein and Gannot, 2002).In most applications, the GMM model is used to train the acoustical model or the speaker model or for noise compensation ...
Robust Muscle Activity Onset Detection Using an ...
The GMM consists of two Gaussian distributions, modeling either noise or surface EMG signals. Such machine learning based techniques have recently demonstrated their superiority in discriminating speech signal from background noise for voice activity detection [19–21]. In this study, the unsupervised learning based on a sequential GMM was ......
 Speech Activity Detection on YouTube Using Deep Neural ...
Speech activity detection (SAD) is an important first step in speech processing. Commonly used methods (e.g., frame-level classification using gaussian mixture models (GMMs)) work well under stationary noise conditions, but do not generalize well to domains such as YouTube, where videos may exhibit a diverse range of environmental conditions....
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