In this paper, we present an extension of a novel continuous residual-based vocoder for statistical parametric speech synthesis. Previous work has shown the advantages of adding envelope modulated noise to the voiced excitation, but this has not been investigated yet in the context of continuous vocoders, i.e. of which all parameters are continuous. The noise component is often not accurately modeled in modern vocoders (e.g. STRAIGHT). For more natural sounding speech synthesis, four time-domain envelopes (Amplitude, Hilbert, Triangular and True) are investigated and enhanced, and then applied to the noise component of the excitation in our continuous vocoder. The performance evaluation is based on the study of time envelopes. In an objective experiment, we investigated the Phase Distortion Deviation of vocoded samples. A MUSHRA type subjective listening test was also conducted comparing natural and vocoded speech samples. Both experiments have shown that the proposed framework using Hilbert and True envelopes provides high-quality vocoding while outperforming the two other envelopes.

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Although there is a significant effort in the design of a selective CDK9/CycT1 inhibitor, no compound has been proven to be a specific inhibitor of this kinase so far. The aim of this research was to develop novel and selective phosphorus containing CDK9/CycT1 inhibitors. Molecules bearing phosphonamidate, phosphonate, and phosphinate moieties were synthesized. Prepared compounds were evaluated in an enzymatic CDK9/CycT1 assay. The most potent molecules were tested in cell-based toxicity and HIV proliferation assays. Selectivity of shortlisted compounds against CDKs and other kinases was tested. The best compound was shown to be a highly specific, ATP-competitive inhibitor of CDK9/CycT1 with antiviral activity.

Recently it was shown that within the Silent Speech Interface (SSI) field, the prediction of F0 is possible from Ultrasound Tongue Images (UTI) as the articulatory input, using Deep Neural Networks for articulatory-to-acoustic mapping. Moreover, text-to-speech synthesizers were shown to produce higher quality speech when using a continuous pitch estimate, which takes non-zero pitch values even when voicing is not present. Therefore, in this paper on UTI-based SSI, we use a simple continuous F0 tracker which does not apply a strict voiced / unvoiced decision. Continuous vocoder parameters (ContF0, Maximum Voiced Frequency and Mel-Generalized Cepstrum) are predicted using a convolutional neural network, with UTI as input. The results demonstrate that during the articulatory-toacoustic mapping experiments, the continuous F0 is predicted with lower error, and the continuous vocoder produces slightly more natural synthesized speech than the baseline vocoder using standard discontinuous F0.

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