Over-Sampling for Accurate Masking Threshold Calculation in Wavelet Packet Audio Coders

Many existing audio coders use a critically sampled discrete wavelet transform (DWT) for the decomposition of audio signals. While the aliasing present in the wavelet coefficients is cancelled in the decoder, these coders normally perform calculation of the simultaneous masking threshold directly on these aliased coefficients. This paper uses over-sampling in the wavelet packet decomposition in order to provide alias-free coefficients for accurate simultaneous masking threshold calculation. The proposed technique is compared with masking threshold calculation based upon the FFT and critically-sampled wavelet coefficients, and the results show that a bit rate saving of up to 16 kbit/s can be achieved using over-sampling

Analysis of orientation error of triaxial accelerometers on the assessment of energy expenditure

This paper investigates the effects of orientation error in the positioning of triaxial accelerometers on the assessment of energy expenditure. Four subjects walked on a treadmill at varying velocities ranging from 4km.h -1 to 5km.h-1. During each test, a triaxial accelerometer attached to the lower back at arbitrary orientations to record body accelerations. Energy expenditure was estimated by the sum of the integrals of the absolute value of accelerometer output from all the three measurement directions. Based on theoretical analysis and experimental observations, it is concluded that small orientation errors ( < 3° ) have no distinguishable effects on the estimation of energy expenditure. We propose an efficient method to compensate for larger orientation errors. The experimental results verified the effectiveness of this proposed compensation method. ©2005 IEEE

Forward masking threshold estimation using neural networks and its application to parallel speech enhancement

Forward masking models have been used successfully in speech enhancement and audio coding. Presently, forward masking thresholds are estimated using simplified masking models which have been used for audio coding and speech enhancement applications. In this paper, an accurate approximation of forward masking threshold estimation using neural networks is proposed. A performance comparison to the other existing masking models in speech enhancement application is presented. Objective measures using PESQ demonstrates that our proposed forward masking model, provides significant improvements (5-15 %) over four existing models, when tested with speech signals corrupted by various noises at very low signal to noise ratios. Moreover, a parallel implementation of the speech enhancement algorithm was developed using Matlab parallel computing toolbox

Forward masking threshold estimation using neural networks and its application to parallel speech enhancement

Forward masking models have been used successfully in speech enhancement and audio coding. Presently, forward masking thresholds are estimated using simplified masking models which have been used for audio coding and speech enhancement applications. In this paper, an accurate approximation of forward masking threshold estimation using neural networks is proposed. A performance comparison to the other existing masking models in speech enhancement application is presented. Objective measures using PESQ demonstrates that our proposed forward masking model, provides significant improvements (5-15 %) over four existing models, when tested with speech signals corrupted by various noises at very low signal to noise ratios. Moreover, a parallel implementation of the speech enhancement algorithm was developed using Matlab parallel computing toolbox

Estimation of walking energy expenditure by using support vector regression

This paper develops a new predictor of walking energy expenditure from wireless measurements of body movements using triaxial accelerometers. Reliable data were collected from repeated walking experiments in different conditions on a treadmill with simultaneous measurement of expired oxygen and carbon dioxide. Support vector regression, a powerful non-linear regression method, was used to process and model the data. This novel processing method sets this investigation apart from existing papers. Good results were achieved in the robust estimation of walking related energy expenditure from a number of variables derived from triaxial accelerometer and treadmill speed. ©2005 IEEE

Experimental Study and Analysis of a Polymer Fiber Bragg Grating Embedded in a Composite Material

The characteristics of polymer fiber Bragg gratings (FBGs) embedded in composite materials are studied in this paper and are compared with characteristics of their silica counterparts. A polymer FBG of 10 mm length which exhibits a peak reflected wavelength circa 1530 nm is fabricated and characterized for this purpose. A silica FBG with a peak reflected wavelength circa 1553 nm is also embedded in the composite material for a comparison study. The fabricated composite material sample with embedded sensors is subjected to temperature and strain changes and the corresponding effects on the embedded polymer and silica FBGs are studied. The measured temperature sensitivity of the embedded polymer FBG was close to that of the same polymer FBG in free space, while the silica FBG shows elevated temperature sensitivity after embedding.With an increase in temperature, spectral broadening was observed for the embedded polymer FBG due to the stress induced by the thermal expansion of the composite material. From the observed wavelength shift and spectral bandwidth change of the polymer FBG, temperature and thermal expansion effects in the composite material can be measured simultaneously

Auditory modelling for speech processing in the perceptual domain

The human hearing system is the most robust speech processor despite noisy environments. This work presents a new computational model for our auditory system by exploring the psychoacoustical masking properties. The model is then applied to speech coding in the perceptual domain. The coding algorithm is capable of producing high quality coded speech and audio, which account for temporal as well as spectral details. The proposed filterbank is also applied to speech denoising in the perceptual domain. The enhanced speech is of good perceptual quality