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This paper presents a robust approach to improve the performance of voice activity detector (VAD) in low signal-to-noise ratio (SNR) noisy environments. To this end, we first generate sparse representations by Bregman Iteration based sparse decomposition with a learned over-complete dictionary, and derive a kind of audio feature called sparse power spectrum(More)
Acoustic environment recognition has been widely used in many applications, and is a considerable difficult problem for the real-life and complex environment. This paper proposes a novel feature, named minimum statistics project coefficients (MSPC), and intents to solve this problem. The MSPC feature is extracted from the background sound which is more(More)
As a promising technique, sparse representation has been extensively investigated in signal processing community. Recently, sparse representation is widely used for speech processing in noisy environments; however, many problems need to be solved because of the particularity of speech. One assumption for speech denoising with sparse representation is that(More)
The sensitivity-field distribution of sensors in the electrical capacitance tomography (ECT) system is influenced by the distribution of multiphase-flow media, and the soft-field characteristics can bring great difficulty into image reconstruction. The subject investigated of this paper is major in the ECT system of 8-electrode oil-water two-phase flow.(More)
The maximum a posteriori (MAP) criterion is broadly used in the statistical model-based voice activity detection (VAD) approaches. In the conventional MAP criterion, however, the inter-frame correlation of the voice activity is not taken into consideration. In this paper, we proposes a novel modified MAP criterion based on a two-state hidden Markov model(More)
This study presents a robust audio retrieval method and discusses its control strategy. In the method, the retrieval target is divided into short segments, each segment is searched respectively and a retrieval window is used to maintain a list of segments that can be searched simultaneously. The method can quickly detect and locate known sound in real-time(More)
A method for confidence measure (CM) using syllable based confidence features is proposed to improve false-alarm rejection of the mandarin keyword spotting (KWS). The features take advantage of the merit of mandarin syllable structure and describe the confidences in every sub-syllable level. The evaluation is processed with support vector machine (SVM) on(More)
a novel audio retrieval method based on negativity judgment is proposed. The foundation is that the similar audio feature vectors should be near after a transform procedure but which is a necessary condition but not sufficient condition to judge whether two audio segments are similar or not. So, it is reasonable to exclude audio vectors that can’t(More)