Nanjing University of Science and Technology

About: Nanjing University of Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Control theory & Catalysis. The organization has 31581 authors who have published 36390 publications receiving 525474 citations. The organization is also known as: Nánjīng Lǐgōng Dàxué & Nánlǐgōng.

CN-Celeb: A Challenging Chinese Speaker Recognition Dataset

Abstract: Recently, researchers set an ambitious goal of conducting speaker recognition in unconstrained conditions where the variations on ambient, channel and emotion could be arbitrary. However, most publicly available datasets are collected under constrained environments, i.e., with little noise and limited channel variation. These datasets tend to deliver over-optimistic performance and do not meet the request of research on speaker recognition in unconstrained conditions.In this paper, we present CN-Celeb, a large-scale speaker recognition dataset collected ‘in the wild’. This dataset contains more than 130,000 utterances from 1,000 Chinese celebrities, and covers 11 different genres in real world. Experiments conducted with two state-of-the-art speaker recognition approaches (i-vector and x-vector) show that the performance on CN-Celeb is far inferior to the one obtained on Vox-Celeb, a widely used speaker recognition dataset. This result demonstrates that in real-life conditions, the performance of existing techniques might be much worse than it was thought. Our database is free for researchers and can be downloaded from http://project.cslt.org.

van der Waals Stacking Induced Transition from Schottky to Ohmic Contacts: 2D Metals on Multilayer InSe

Abstract: Incorporation of two-dimensional (2D) materials in electronic devices inevitably involves contact with metals, and the nature of this contact (Ohmic and/or Schottky) can dramatically affect the electronic properties of the assembly. Controlling these properties to reliably form low-resistance Ohmic contact remains a great challenge due to the strong Fermi level pinning (FLP) effect at the interface. Herein, we employ density functional theory calculations to show that van der Waals stacking can significantly modulate Schottky barrier heights in the contact formed between multilayer InSe and 2D metals by suppressing the FLP effect. Importantly, the increase of InSe layer number induces a transition from Schottky to Ohmic contact, which is attributed to the decrease of the conduction band minimum and rise of the valence band maximum of InSe. Based on the computed tunneling and Schottky barriers, Cd3C2 is the most compatible electrode for 2D InSe among the materials studied. This work illustrates a straightforward method for developing more effective InSe-based 2D electronic nanodevices.

MPED: A Multi-Modal Physiological Emotion Database for Discrete Emotion Recognition

Abstract: To explore human emotions, in this paper, we design and build a multi-modal physiological emotion database, which collects four modal physiological signals, i.e., electroencephalogram (EEG), galvanic skin response, respiration, and electrocardiogram (ECG). To alleviate the influence of culture dependent elicitation materials and evoke desired human emotions, we specifically collect an emotion elicitation material database selected from more than 1500 video clips. By the considerable amount of strict man-made labeling, we elaborately choose 28 videos as standardized elicitation samples, which are assessed by psychological methods. The physiological signals of participants were synchronously recorded when they watched these standardized video clips that described six discrete emotions and neutral emotion. With three types of classification protocols, different feature extraction methods and classifiers (support vector machine and k-NearestNeighbor) were used to recognize the physiological responses of different emotions, which presented the baseline results. Simultaneously, we present a novel attention-long short-term memory (A-LSTM), which strengthens the effectiveness of useful sequences to extract more discriminative features. In addition, correlations between the EEG signals and the participants' ratings are investigated. The database has been made publicly available to encourage other researchers to use it to evaluate their own emotion estimation methods.