Single-Channel Speech Dereverberation using Subband Network with A Reverberation Time Shortening Target

This work proposes a subband network for single-channel speech dereverberation, and also a new learning target based on reverberation time shortening (RTS). In the time-frequency domain, we propose to use a subband network to perform dereverberation for different frequency bands independently. The time-domain convolution can be well decomposed to subband convolutions, thence it is reasonable to train the subband network to perform subband deconvolution. The learning target for dereverberation is usually set as the direct-path speech or optionally with some early reflections. This type of target suddenly truncates the reverberation, and thus it may not be suitable for network training, and leads to a large prediction error. In this work, we propose a RTS learning target to suppress reverberation and meanwhile maintain the exponential decaying property of reverberation, which will ease the network training, and thus reduce the prediction error and signal distortions. Experiments show that the subband network can achieve outstanding dereverberation performance, and the proposed target has a smaller prediction error than the target of direct-path speech and early reflections.Comment: Submitted to INTERSPEECH 202

Social and Emotional Learning Difficulties of Refugee High School Students in an After-school Tutoring Program

School-aged children constitute a significant portion of the large number of refugees who have resettled in Canada in recent years. Due to the lack of cross-cultural competencies, a social justice focus, and transformative leadership skills, Canadian schools are often challenged to effectively address refugee students’ socio-psychological problems. Moreover, educational literature and policy, which specifically target Canadian refugee students, are scarce. To help with the issue, this study examined eight refugee high school students through an online after-school tutoring program and evaluated their performances in the five domains of social-emotional learning competencies: social awareness, self-management, relationship skills, responsible decision making, and social awareness. The two researchers participated in this study as tutors and adopted observation as the main approach. Findings of the study revealed that refugee students’ performances in these skills was not optimal, in general. Especially, there is a high demand in improving the refugee students’ self-awareness, self-management, and responsible decision-making. Most of them had good relationship skills as well as social awareness. Also, all the social-emotional learning skills connect closely with the refugee students’ academic success

Grain Boundary Effects on Microstructural Stability of Nanocrystalline Metallic Materials

Grain boundaries play an important role in dictating the mechanical and physical properties of nanocrystalline (NC) materials because of the increased volume fraction of intercrystalline components as the grain size decreases. In general, grain boundaries have a high energy level and there exists a thermodynamic driving force to reduce the overall area of grain boundaries through grain coarsening, making NC material systems intrinsically unstable. Recent investigations also indicate that mechanical deformation can promote grain growth in NC material even at the cryogenic temperatures. In this chapter, first, the current investigation on the grain boundary structures of NC metallic materials is briefly reviewed and then the state-of-the-art of experimental results on the microstructural stability during deformation processes is discussed. Finally, several key issues for improving the microstructure stability of NC metallic materials and possible future work are discussed

xFx_F Dependence of Drell-Yan Transverse Moemtum Broadening

We analyze $x_F$ dependence of Drell-Yan transverse momentum broadening in hadron-nucleus collisions. In terms of generalized factorization theorem, we show that the $x_F$ dependence of transverse momentum broadening, $\Delta < q_T^2 > (x_F)$, can be calculated in perturbative QCD. We demonstrate that $\Delta (x_F)$ is a good observable for studying the effects of initial-state multiple scattering and extracting quark-gluon correlation functions.Comment: 10 pages, 3 figure

TweetsCOV19 -- A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic

Publicly available social media archives facilitate research in the social sciences and provide corpora for training and testing a wide range of machine learning and natural language processing methods. With respect to the recent outbreak of the Coronavirus disease 2019 (COVID-19), online discourse on Twitter reflects public opinion and perception related to the pandemic itself as well as mitigating measures and their societal impact. Understanding such discourse, its evolution, and interdependencies with real-world events or (mis)information can foster valuable insights. On the other hand, such corpora are crucial facilitators for computational methods addressing tasks such as sentiment analysis, event detection, or entity recognition. However, obtaining, archiving, and semantically annotating large amounts of tweets is costly. In this paper, we describe TweetsCOV19, a publicly available knowledge base of currently more than 8 million tweets, spanning October 2019 - April 2020. Metadata about the tweets as well as extracted entities, hashtags, user mentions, sentiments, and URLs are exposed using established RDF/S vocabularies, providing an unprecedented knowledge base for a range of knowledge discovery tasks. Next to a description of the dataset and its extraction and annotation process, we present an initial analysis and use cases of the corpus