Naver Corporation

About: Naver Corporation is a company organization based out in Seongnam-si, South Korea. It is known for research contribution in the topics: Terminal (electronics) & Computer science. The organization has 4038 authors who have published 4294 publications receiving 35045 citations. The organization is also known as: NAVER Corporation & NAVER.

Replay Spoofing Detection System for Automatic Speaker Verification Using Multi-Task Learning of Noise Classes

Abstract: In this paper, we propose a replay attack spoofing detection system for automatic speaker verification using multi-task learning of noise classes. We define the noise that is caused by the replay attack as replay noise. We explore the effectiveness of training a deep neural network simultaneously for replay attack spoofing detection and replay noise classification. The multi-task learning includes classifying the noise of playback devices, recording environments, and recording devices as well as the spoofing detection. Each of the three types of the noise classes also includes a genuine class. The experiment results on the version 1.0 of ASVspoof2017 datasets demonstrate that the performance of our proposed system is improved by 30% relatively on the evaluation set.

Classification Scheme of Unstructured Text Document using TF-IDF and Naive Bayes Classifier

Abstract: Recently due to large-scale data spread in digital economy, the era of big data is coming. Through big data, unstructured text data consisting of technical text document, confidential document, false information documents are experiencing serious problems in the runoff. To prevent this, the need of art to sort and process the document consisting of text data has increased. In this paper, we propose a novel text classification scheme which learns some data sets and correctly classifies unstructured text data into two different categories, True and False. The proposed method is implemented using Naive Bayes document classifier and TF-IDF.

SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder

Abstract: Designing a lightweight and robust portrait segmentation algorithm is an important task for a wide range of face applications. However, the problem has been considered as a subset of the object segmentation and less handled in this field. Obviously, portrait segmentation has its unique requirements. First, because the portrait segmentation is performed in the middle of a whole process, it requires extremely lightweight models. Second, there has not been any public datasets in this domain that contain a sufficient number of images. To solve the first problem, we introduce the new extremely lightweight portrait segmentation model SINet, containing an information blocking decoder and spatial squeeze modules. The information blocking decoder uses confidence estimation to recover local spatial information without spoiling global consistency. The spatial squeeze module uses multiple receptive fields to cope with various sizes of consistency. To tackle the second problem, we propose a simple method to create additional portrait segmentation data, which can improve accuracy. In our qualitative and quantitative analysis on the EG1800 dataset, we show that our method outperforms various existing lightweight models. Our method reduces the number of parameters from 2.1M to 86.9K (around 95.9% reduction), while maintaining the accuracy under an 1% margin from the state-of-the-art method. We also show our model is successfully executed on a real mobile device with 100.6 FPS. In addition, we demonstrate that our method can be used for general semantic segmentation on the Cityscapes dataset. The code and dataset are available in https://github.com/HYOJINPARK/ExtPortraitSeg.

The Effects of Maternal Emotional Availability on Preschooler’s Social Skills and Problem Behaviors: The Mediating Effects of Preschooler’s Effortful Control

Abstract: The purpose of this study was to explore the mediating effects of preschooler`s effortful control on the relationship between maternal emotional availability and preschooler`s social skills and problem behaviors. One hundred-thirty six 5-year-old preschoolers and their mothers participated in this study. Instruments for this study were the Emotional Availability Scale for maternal emotional availability, the Delay task, and the Child Behavior Questionnaire for preschooler`s effortful control, and the Social Skill Rating Scale, K-CBCL 1.5-5 and K-TRF for preschooler`s social skills and problem behaviors. The resulting data were analyzed using descriptive statistics, partial correlation, and structural equation modeling analysis. As predicted, the preschooler`s effortful control mediated the effects of maternal emotional availability on preschooler`s social skills and problem behaviors. In conclusion, the preschooler`s effortful control mediates the effects of emotion related socialization behavior on the preschooler`s socio-emotional adjustment.

Method and system for processing personal data base on block chain

Abstract: The present invention provides a method for processing personal data based on a block chain and a system thereof. According to embodiments of the present invention, the method for processing personal data utilizes a personal identification key in a block chain network registered for a user in different services identifying the same user by different identifiers and provides personal data for the corresponding user on the block chain network, thereby tracking and utilizing the personal data for the corresponding user in the different services through the personal identification key. The method for processing personal data of a medium comprises the following steps of: managing the identifier of a member registered in the medium; interlocking the personal identification key which is issued by the block chain network by the member and identifies the user corresponding to the member with the identifier; and transmitting a block to participants of the block chain network by using the personal identification key so that the block including data related to an activity of the member is connected to the block chain.