Selective Kernel Attention for Robust Speaker Verification

Recent state-of-the-art speaker verification architectures adopt multi-scale processing and frequency-channel attention techniques. However, their full potential may not have been exploited because these techniques' receptive fields are fixed where most convolutional layers operate with specified kernel sizes such as 1, 3 or 5. We aim to further improve this line of research by introducing a selective kernel attention (SKA) mechanism. The SKA mechanism allows each convolutional layer to adaptively select the kernel size in a data-driven fashion based on an attention mechanism that exploits both frequency and channel domain using the previous layer's output. We propose three module variants using the SKA mechanism whereby two modules are applied in front of an ECAPA-TDNN model, and the other is combined with the Res2Net backbone block. Experimental results demonstrate that our proposed model consistently outperforms the conventional counterpart on the three different evaluation protocols in terms of both equal error rate and minimum detection cost function. In addition, we present a detailed analysis that helps understand how the SKA module works.Comment: Submitted to INTERSPEECH 2022. 5 pages, 3 figures, 1 tabl

Fully Unsupervised Training of Few-shot Keyword Spotting

For training a few-shot keyword spotting (FS-KWS) model, a large labeled dataset containing massive target keywords has known to be essential to generalize to arbitrary target keywords with only a few enrollment samples. To alleviate the expensive data collection with labeling, in this paper, we propose a novel FS-KWS system trained only on synthetic data. The proposed system is based on metric learning enabling target keywords to be detected using distance metrics. Exploiting the speech synthesis model that generates speech with pseudo phonemes instead of texts, we easily obtain a large collection of multi-view samples with the same semantics. These samples are sufficient for training, considering metric learning does not intrinsically necessitate labeled data. All of the components in our framework do not require any supervision, making our method unsupervised. Experimental results on real datasets show our proposed method is competitive even without any labeled and real datasets.Comment: Accepted by IEEE SLT 202

Prognostic Factors and Clinical Outcomes of High-Dose Chemotherapy followed by Autologous Stem Cell Transplantation in Patients with Peripheral T Cell Lymphoma, Unspecified: Complete Remission at Transplantation and the Prognostic Index of Peripheral T Cell Lymphoma Are the Major Factors Predictive of Outcome

AbstractHigh-dose chemotherapy followed by autologous stem cell transplantation (HDT/ASCT) offers a rescue option for T cell lymphoma patients with poor prognosis. However, the effectiveness of HDT/ASCT in patients with various peripheral T cell subtypes, optimal transplant timing, and the prognostic factors that predict better outcomes, have not been identified. We retrospectively investigated the clinical outcomes and prognostic factors for HDT/ASCT in 64 Korean patients with peripheral T cell lymphoma, unspecified (PTCL-U) between March 1995 and February 2007. The median age at transplantation was 44 years (range: 15-63 years). According to the age-adjusted International Prognostic Index (a-IPI) and the prognostic index of PTCL (PIT), 8 patients (12.5%) were in the high-risk group and 16 (26.6%) had the 2-3 PIT factors, respectively. After a median follow-up of 29.7 months, the 3-year overall survival (OS) and progression-free survival (PFS) rates were 53.0% ± 7.5% and 44.3% ± 7.0%, respectively. Univariate analysis showed that poor performance status, high lactate dehydrogenase (LDH) levels, high a-IPI score, high PIT classes, failure to achieve complete response (CR) at transplantation, and nonfrontline transplantation were associated with poor OS. Multivariate analysis showed that failure to achieve CR at transplantation (hazard ratio [HR] 2.23; 95% confidence interval [CI] 1.78-7.93) and 2-3 PIT factors (HR 3.76; 95% CI 1.02-5.42) were independent prognostic factors for OS. Failure to achieve CR at transplantation and high PIT are negative predictable factors for survival following HDT/ASCT in patients with PTCL-U

Effects of Polyethylene Glycol-Induced Water Stress on the Physiological and Biochemical Responses of Different Sorghum Genotypes

Globally, abiotic stress is the primary cause of crop loss, reducing the average yields of most major crop plants by more than 50% (Bray et. al., 2000). Drought stress is one of the most widespread environmental stresses when the total area of arable land is classified according to the occurrence of various stress factors (Arora et al., 2002). Drought and other abiotic stresses limit the photosynthetic activity of various crops, which in turn reduces the production of photosynthetic assimilates. Almost every developmental stage of the plant is affected by water stress. However, it has been observed that drought stress is more damaging to plants at the growth and germination stages, affecting seedling shoot length, flowering, and root length (Khayatnezhad, et al., 2010

A Protein Profile of Visceral Adipose Tissues Linked to Early Pathogenesis of Type 2 Diabetes Mellitus

Adipose tissue is increasingly recognized as an endocrine organ playing important pathophysiological roles in metabolic abnormalities, such as obesity, cardiovascular disease, and type 2 diabetes mellitus (T2DM). In particular, visceral adipose tissue (VAT), as opposed to subcutaneous adipose tissue, is closely linked to the pathogenesis of insulin resistance and T2DM. Despite the importance of VAT, its molecular signatures related to the pathogenesis of T2DM have not been systematically explored. Here, we present comprehensive proteomic analysis of VATs in drug-naïve early T2DM patients and subjects with normal glucose tolerance. A total of 4,707 proteins were identified in LC-MS/MS experiments. Among them, 444 increased in abundance in T2DM and 328 decreased. They are involved in T2DM-related processes including inflammatory responses, peroxisome proliferator-activated receptor signaling, oxidative phosphorylation, fatty acid oxidation, and glucose metabolism. Of these proteins, we selected 11 VAT proteins that can represent alteration in early T2DM patients. Among them, up-regulation of FABP4, C1QA, S100A8, and SORBS1 and down-regulation of ACADL and PLIN4 were confirmed in VAT samples of independent early T2DM patients using Western blot. In summary, our profiling provided a comprehensive basis for understanding the link of a protein profile of VAT to early pathogenesis of T2DM. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.1

A test of the submentalizing hypothesis : apes' performance in a false belief task inanimate control

Financial support came from Ministry of Education, Culture, Sports, Science and Technology (K-CONNEX to FK), Japan Society for Promotion of Science (KAKENHI 26885040, 16K21108 to FK), JSPS (KAKENHI 26245069, 24000001 to SH), and European Research Council (Synergy grant 609819 SOMICS to JC).Much debate concerns whether any nonhuman animals share with humans the ability to infer others' mental states, such as desires and beliefs. In a recent eye-tracking false-belief task, we showed that great apes correctly anticipated that a human actor would search for a goal object where he had last seen it, even though the apes themselves knew that it was no longer there. In response, Heyes proposed that apes' looking behavior was guided not by social cognitive mechanisms but rather domain-general cueing effects, and suggested the use of inanimate controls to test this alternative submentalizing hypothesis. In the present study, we implemented the suggested inanimate control of our previous false-belief task. Apes attended well to key events but showed markedly fewer anticipatory looks and no significant tendency to look to the correct location. We thus found no evidence that submentalizing was responsible for apes' anticipatory looks in our false-belief task.Publisher PDFPeer reviewe