Speech assessment is crucial for many applications, but current intrusive methods cannot be used in real environments. Data-driven approaches have been proposed, but they use simulated speech materials or only estimate objective scores. In this paper, we propose a novel multi-task non-intrusive approach that is capable of simultaneously estimating both subjective and objective scores of real-world speech, to help facilitate learning. This approach enhances our prior work, which estimated subjective mean-opinion scores, where our approach now operates directly on the time-domain signal in an end-to-end fashion. The proposed system is compared against several state-of-the-art systems. The experimental results show that our multi-task and end-to-end framework leads to higher correlation performance and lower prediction errors, according to multiple evaluation measures.
A reliable and accurate liquid chromatography with evaporative light scattering detection (LC-ELSD) method was developed for simultaneous determination of five constituents in Xue-Fu-Zhu-Yu capsule, a widely used prescription of traditional Chinese medicine (TCM). The chromatographic separation was performed on a Symmetry C 18 column (150 mmÂ4.6 mm, 5.0 μm) using gradient elution of acetonitrile and water (containing 1.0% acetic acid). The flow rate was 0.6 mL/min and the temperature of column was 30°C. A good linearity correlation was obtained over the investigated concentration ranges. Recoveries of the five components varied from 97.31% to 99.84% (RSD < 4.0%). The validated method was successfully applied to the quality assessment of Xue-FuZhu-Yu capsule.
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