A Development Strategy for Afghanistan: Lessons of an Employment Policy Mission

This article has addressed itself to the delicate problem of evolving a development and employment strategy for a country still at its early stages of development and with traditional socio-economic structures. To modernise these structures and thus assist in achieving fuller and more productive employment, in reducing poverty and income inequality and in satisfying the basic needs of the mass of the population, the article based on the conclusions and recommendations of an ILO Mission has recommended a fourpronged attack: (1) a particular stress on rural development; (2) an urban strategy aiming at increasing the potential of the informal sector and at stimulating the rapid development of the industrial sector; (3) appropriate education, training and labour market policies; (4) finally, reforms in development planning and administration

Noise Reduction Using Wavelet Thresholding of Multitaper Estimators and Geometric Approach to Spectral Subtraction for Speech Coding Strategy

ObjectivesNoise reduction using wavelet thresholding of multitaper estimators (WTME) and geometric approach to spectral subtraction (GASS) can improve speech quality of noisy sound for speech coding strategy. This study used Perceptual Evaluation of Speech Quality (PESQ) to assess the performance of the WTME and GASS for speech coding strategy.MethodsThis study included 25 Mandarin sentences as test materials. Environmental noises including the air-conditioner, cafeteria and multi-talker were artificially added to test materials at signal to noise ratio (SNR) of -5, 0, 5, and 10 dB. HiRes 120 vocoder WTME and GASS noise reduction process were used in this study to generate sound outputs. The sound outputs were measured by the PESQ to evaluate sound quality.ResultsTwo figures and three tables were used to assess the speech quality of the sound output of the WTME and GASS.ConclusionThere is no significant difference between the overall performance of sound quality in both methods, but the geometric approach to spectral subtraction method is slightly better than the wavelet thresholding of multitaper estimators

Estimating acoustic speech features in low signal-to-noise ratios using a statistical framework

Accurate estimation of acoustic speech features from noisy speech and from different speakers is an ongoing problem in speech processing. Many methods have been proposed to estimate acoustic features but errors increase as signal-to-noise ratios fall. This work proposes a robust statistical framework to estimate an acoustic speech vector (comprising voicing, fundamental frequency and spectral envelope) from an intermediate feature that is extracted from a noisy time-domain speech signal. The initial approach is accurate in clean conditions but deteriorates in noise and with changing speaker. Adaptation methods are then developed to adjust the acoustic models to the noise conditions and speaker. Evaluations are carried out in stationary and nonstationary noises and at SNRs from -5dB to clean conditions. Comparison with conventional methods of estimating fundamental frequency, voicing and spectral envelope reveals the proposed framework to have lowest errors in all conditions tested

Spectral masking and filtering

International audienc