A Spectral Conversion Approach to Feature Denoising and Speech Enhancement

In this paper we demonstrate that spectral conversion can be successfully applied to the speech enhancement problem as a feature denoising method. The enhanced spectral features can be used in the context of the Kalman filter for estimating the clean speech signal. In essence, instead of estimating the clean speech features and the clean speech signal using the iterative Kalman filter, we show that is more efficient to initially estimate the clean speech features from the noisy speech features using spectral conversion (using a training speech corpus) and then apply the standard Kalman filter. Our results show an average improvement compared to the iterative Kalman filter that can reach 6 dB in the average segmental output Signal-to-Noise Ratio (SNR), in low input SNR\u27s

Ultrasound image denoising via maximum a posteriori estimation of wavelet coefficients

Abstract — Speckle noise removal by means of digital image processors could improve the diagnostic potential of medical ultrasound. This paper addresses the speckle suppression issue within the framework of wavelet analysis. As a first step of our approach, the logarithm of the original image is decomposed into several scales through a multiresolution analysis employing the 2-D wavelet transform. Then, we design a maximum a posteriori (MAP) estimator, which relies on a recently introduced statistical representation for the wavelet coefficients of ultrasound images [1]. We use an alpha-stable model to develop a blind noise-removal processor that performs a non-linear operation on the data. Finally, we compare our technique to current state-of-the-art denoising methods applied on actual ultrasound images and we find it more effective, both in terms of speckle reduction and signal detail preservation

THE IMPACT OF HEALTH INSURANCE ON THE ACCESS TO HEALTH CARE AND FINANCIAL PROTECTION IN RURAL AREAS OF DEVELOPING COUNTRIES: CASE STUDY SENEGAL

Access to public and private health insurance in rural areas of low income countries is severely constrained by high unit cost of transaction per contract due to information asymmetries between insurance sellers and buyers. This leads to a situation in which the majority of the poor have to rely on out-of-pocket expenditures when they are ill, resulting in a high vulnerability for health shocks which negatively affect the overall risk management of the household, investment and resource allocation decisions. Recently, however, in various parts of the world community based health insurance schemes have emerged and are becoming increasingly recognized as an instrument to finance health care in poor developing countries. These mutual insurance schemes often develop out of micro-finance institutions such as the Grameen Bank in Bangladesh and are based on similar principles, i.e. relying on collective shared norms, solidarity and enforcement by peers. Taking the example of "les mutuelles de santés" (mutual health organization) in rural Senegal this paper analyzes weather or not members in a mutual health insurance scheme have actually a better access to health care than non-members. A binary probit model is estimated for the determinants of participation in a mutual and a logit/log linear model is used to measure the impact on health care utilization and financial protection. Impact is measured in terms of (a) access to health care facilities, i.e. if members frequent health facilities more often than non-members controlling for age, sex, education and the frequency of illness, which capture the need for health care and the health status and (b) the amount of out-of-pocket payments in case of health care use. The results show that while the health insurance schemes reach otherwise excluded people, the poorest of the poor in the communities are not covered. As important determinants for being a member beside income, we find that religion, belonging to a certain ethnic group, access to social capital and community characteristics are important. Regarding the impact on the access to health care, members of a mutual have better access to health care services than non-members after controlling for common individual, household and community characteristics. The probability of making use of hospitalization increases by 2 %-age points with membership and expenditure in case of need is reduced by about 50% compared with non-members. Given the results from this study, community financing schemes have the potential to improve existing the risk management capacity of rural households. To reduce identified limitations of the schemes, an enlargement of the risk pool and a scaling up/linking of the schemes is, however, a prerequisite. Appropriate instruments to be further tested should include re-insurance policies, subsidies for the poorest and developing linkages to the private sector via the promotion of group insurance policies. All these instruments call for a stronger role of public health policy in rural areas of low income countries