Human speech perception withstands a wide variety of distortions, both experimentally applied and naturallyoccurring. A novel approach to these situations in robust ASR identifies the spectro-temporal regions which carry reliable speech evidence and treats the remainder as missing or uncertain. This standpoint makes minimal assumptions about any noise background. This paper describes two approa...

This paper investigates the problem of automatic segmentation of speech recorded in noisy channel corrupted environments. Using an HMM-based speech segmentation algorithm, speech enhancement and parameter compensation techniques previously proposed for robust speech recognition are evaluated and compared for improved segmentation in colored noise. Speech enhancement algorithms considered includ...

Motion analysis of moving targets is an important issue in several applications such as video surveillance or robotics. Background subtraction is one of the simplest and widely used techniques for moving target detection in video sequences. In this paper, we investigate the advantages of using a multispectral video acquisition system of more than three bands for background subtraction over the ...

We show that two superimposed time-and-space-domain holograms in a persistent spectral hole-burning material can produce destructive interference, even if the path-length difference of the writing beams is constant. The cancellation of the amplitudes in the 21 diffraction order occurs when the two holograms have specially chosen spectral envelopes that represent a pair of complementary function...

In this paper we present a two stage noise reduction algorithm for speech enhancement. The speech noise removal algorithm is based on a two stage noise filtering LSAHT by log spectral amplitude speech estimator (LSA) and harmonic tunneling (HT) with spectral subtraction. The performance of the system is measured by the segmental signal-to-noise ratio, mean opinion score (MOS) tests, and the rec...

This paper is the final report of the EECS451 project. In this project, several audio enhancement methods are researched and implemented in MATLAB to reduce the noise in poorly recorded speech and reach a better signal-to-noise ratio. Improvement is applied to the basic spectral reduction algorithms. Issues of the trade off in this method and side effect included are also discussed. Keywords—Bu...

This paper addresses the study of the speech intelligibility enhancement. The speech model, noise sources, perceptual aspects of speech, and performance evaluation are reviewed. The intelligibility enhancement system based on spectral subtraction technique is investigated. Spectral density estimation device based on the algorithm of smoothed periodograms is analysed. Determination of the silenc...

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared ...

This paper establishes an infrared spectral identification key for five natural resins (shellac, sandarac, mastic, copal and rosin) based on their absorbance band positions. These resins may be identified when used in mixtures, such as furniture finishes, at concentrations as low as 1%. Computer methods of deconvolution and spectral subtraction are used to augment this process. The method was v...