In this paper, we propose a neural articulation-to-speech (ATS) framework that synthesizes high-quality speech from articulatory signal in a multi-speaker situation. Most conventional ATS approaches only focus on modeling contextual information of speech from a single speaker's articulatory features. To explicitly represent each speaker's speaking style as well as the contextual information, our proposed model estimates style embeddings, guided from the essential speech style attributes such as pitch and energy. We adopt convolutional layers and transformer-based attention layers for our model to fully utilize both local and global information of articulatory signals, measured by electromagnetic articulography (EMA). Our model significantly improves the quality of synthesized speech compared to the baseline in terms of objective and subjective measurements in the Haskins dataset.
Cancer survival rates are improving, and the focus is moving toward quality survival. Fertility is a key aspect of quality of life for cancer patients of childbearing age. Although cancer treatment may impair fertility, some patients may benefit from referral to a specialist before treatment. However, the majority of studies examining patient recall of discussion and referral for fertility preservation (FP) show that less than half receive this information. This study examined the referral practices of oncologists in the United States.This study examined oncologists' referral practice patterns for FP among US physicians using the American Medical Association Physician Masterfile database. A 53-item survey was administered via mail and Internet to a stratified random sample of US physicians.Forty-seven percent of respondents routinely refer cancer patients of childbearing age to a reproductive endocrinologist. Referrals were more likely among female physicians (P = .004), those with favorable attitudes (P = .043), and those whose patients routinely ask about FP (odds ratio = 2.09; 95% CI, 1.31 to 3.33).Less than half of US physicians are following the guidelines from the American Society of Clinical Oncology, which suggest that all patients of childbearing age should be informed about FP.
Abstract Background Numerous studies on Alzheimer’s disease (AD) are being undertaken, and there is a plethora of high‐quality clinical data and resources for AD in Korea. However, because the resources and data are not thoroughly standardized, they are challenging to use. The Trial Ready Registry (TRR) and Dementia Platform Korea (DPK) technologies were developed to investigate possible AD therapy targets and biomarkers, as well as to progress the AD research field in Korea by standardizing the dementia dataset in Korea. Method To collect human‐derived materials with MCD, we designed the minimum common dataset (MCD), which includes clinical evaluations, cognitive evaluations, magnetic resonance imaging (MRI), Florbetaben (FBB)‐PET, Flutematamol (FMM)‐PET, and blood tests. Result The TRR‐DPK system is planned to enroll 3,000 participants in MCD exams, blood tests, and brain imaging by 2028. Since 2020, 942 people had been recruited for the system as of December 2022. We collected human‐derived materials such as plasma, serum, DNA, and PBMCs from participants with the purpose of distributing human‐derived materials matched to their brain imaging and clinical data. Conclusion We expect that the TRR‐DPK system will improve AD research by giving researchers access to human‐derived materials and a variety of quality‐controlled data.
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