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This paper describes an enhancement strategy based on several perceptual-assessment criteria for dereverberation algorithms. The complete procedure is applied to an algorithm for reverberant speech enhancement based on single-channel blind spectral subtraction. This enhancement was implemented by combining different quality measures, namely the so-called QAreverb, the speech-to-reverberation modulation...
This paper addresses the problem of anomaly detection on rotating machinery in industrial environments using single channel audio signals. The proposed algorithm is based on image processing feature analysis obtained from the image representation of the Short-time Fourier Transform of reference and degraded audio signals. In order to assess the potential of the algorithm, a 8 signals database is recorded...
This paper investigates the problem of automatic detection of rotating-machine faults based on vibration signals acquired during machine operation. In particular, two new signal features, namely the kurtosis and entropy, are considered along with main spectral peaks to discriminate between several machine conditions: normal operation, (vertical and horizontal) misalignment, unbalanced load and bearing...
This paper describes algorithms for estimating two important features associated with the reverberation effect on speech signals: the reverberation time and direct-to-reverberant energy ratio. Both methods are referred to as blind algorithms in the sense that they are entirely based on the reverberant signal itself, not depending on the knowledge of the clean original signal. Proposed schemes use...
This paper addresses the problem of reducing the reverberation effect from speech signals, which is known as dereverberation. The main idea is to modify a dereverberation algorithm based on ideal channel selection (ICS) from an algorithm with reference to a blind algorithm. The channel selection technique performs a comparison between clean and degraded speech signals to decide the channel selectivity...
The paper addresses the problem of classifying mechanical faults in rotating machines. In this context, three operational classes are considered, namely: normal (where the machine has no fault), unbalance (where the machine load has its weight not equally distributed), and misalignment (where the rotor and machine axes are dislocated from its natural concentric position). A large dataset consisting...
This paper presents a study of the capacity of four speech signal features to assess speech perceptual quality and their use in a typical two-stage algorithm for reverberant speech enhancement. This algorithm is divided into two blocks: one that deals with the coloration effect, due to the early reflections, and the other for reducing the long-term reverberation. The proposed features are skewness,...
This paper addresses the problem of quantifying the reverberation effect in speech signals. The perception of reverberation is assessed based on a new measure combining the characteristics of reverberation time, room spectral variance, and direct-to-reverberant energy ratio, which are estimated from the associated room impulse response (RIR). The practical aspects behind a robust RIR estimation are...
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