Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

Modeling Small Molecule Elution From a Hydrogel using a Microfluidic Technique

Drug release from a fluid-contacting biomaterial is simulated using a microfluidic device with channels defined by solute-loaded hydrogel. In order to mimic a drug delivery device, a solution of poly(ethylene glycol) diacrylate (PEG-DA), solute, and photoinitiator is cured inside a microfluidic device with a channel through the center ofthe hydrogel. As water is pumped through the channel, solute diffuses out of the hydrogel and into the water. Channel sizes within the devices range from 300 µm to 1000 µm to simulate vessels within the body. The properties of the PEG hydrogel were characterizedby the extent of crosslinking, the swelling ratio, and the mesh size of the gel. The structure of the hydrogel was related to the UV exposure dosage and the initial water and solute content in the PEG-DA solution.