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Speech enhancement through voice activity detection using speech absence probability based on Teager energy

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Journal of Central South University 2013年第2期20卷 424-432页

作者： PARKYun-sik lee sang-min Department of Electronic Engineering Inha University Institute for Information and Electronics Research Inha University

In this work, a novel voice activity detection （VAD） algorithm that uses speech absence probability （SAP） based on Teager energy （TE） was proposed for speech enhancement. The proposed method employs local SAP （LSAP） based on the TE of noisy speech as a feature parameter for voice activity detection （VAD） in each frequency subband, rather than conventional LSAP. Results show that the TE operator can enhance the abiTity to discriminate speech and noise and further suppress noise components. Therefore, TE-based LSAP provides a better representation of LSAP, resulting in improved VAD for estimating noise power in a speech enhancement algorithm. In addition, the presented method utilizes TE-based global SAP （GSAP） derived in each frame as the weighting parameter for modifying the adopted TE operator and improving its performance. The proposed algorithm was evaluated by objective and subjective quality tests under various environments, and was shown to produce better results than the conventional method.

关键词： speech enhancement Teager energy speech absence probability voice activity detection

A speech enhancement algorithm to reduce noise and compensate for partial masking effect

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Journal of Central South University 2011年第4期18卷 1121-1127页

作者： JEON Yu-yong lee sang-min Department of Electronic Engineering Inha University Institute for Information and Electronics Research Inha University

To enhance the speech quality that is degraded by environmental noise,an algorithm was proposed to reduce the noise and reinforce the *** minima controlled recursive averaging(MCRA) algorithm was used to estimate the noise spectrum and the partial masking effect which is one of the psychoacoustic properties was introduced to reinforce *** performance evaluation was performed by comparing the PESQ(perceptual evaluation of speech quality) and segSNR(segmental signal to noise ratio) by the proposed algorithm with the conventional *** a result,average PESQ by the proposed algorithm was higher than the average PESQ by the conventional noise reduction algorithm and segSNR was higher as much as 3.2 dB in average than that of the noise reduction algorithm.

关键词： speech enhancement noise reduction psychoacoustic property human hearing property

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Journal of Central South University 2013年第4期20卷 982-987页

作者： lee Myeong-ho 魏荷 lee sang-hyuk lee sang-min SHIN Seung-soo Department of e-Commerce Semyung University Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Institute for Information and Electronics Research Inha University Department of Information Security Tongmyung University

Similarity measure design for discrete data group was proposed. Similarity measure design for continuous membership function was also carried out. Proposed similarity measures were designed based on fuzzy number and distance measure, and were proved. To calculate the degree of similarity of discrete data, relative degree between data and total distribution was obtained. Discrete data similarity measure was completed with combination of mentioned relative degrees. Power interconnected system with multi characteristics was considered to apply discrete similarity measure. Naturally, similarity measure was extended to multi-dimensional similarity measure case, and applied to bus clustering problem.

关键词： similarity measure multi-dimension discrete data relative degree power interconnected system

Fuzzy entropy design for non convex fuzzy set and application to mutual information

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Journal of Central South University 2011年第1期18卷 184-189页

作者： lee sang-Hyuk lee sang-min SOHN Gyo-Yong KIM Jaeh-Yung Department of Electronics Engineering Inha UniversityIncheon 402-751Korea School of Electrical Engineering and Computer Science Kyungpook National UniversityDaegu 702-701Korea School of Mechatronics Changwon National University

Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance *** proposed fuzzy entropy had the same structure as that of convex fuzzy membership *** procedure of fuzzy entropy was proposed by considering fuzzy membership through distance measure,and the obtained results contained more flexibility than the general fuzzy membership ***,characteristic analyses for non convex function were also *** on the mutual information were carried out through the proposed fuzzy entropy and similarity measure,which was also dual structure of fuzzy *** the illustrative example,mutual information was discussed.

关键词： fuzzy entropy non convex fuzzy membership function distance measure similarity measure mutual information

Power interconnected system clustering with advanced fuzzy C-mean algorithm

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Journal of Central South University 2011年第1期18卷 190-195页

作者：王洪梅 KIM Jae-Hyung JUNG Dong-Yean lee sang-min lee sang-Hyuk School of Mechatronics Changwon National University Daeho Tech Co.Ltd. Changwon 641-465Korea Department of Electronics Engineering Inha University

An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.

关键词： fuzzy C-mean similarity measure distance measure interconnected system clustering

Improved speech absence probability estimation based on environmental noise classification

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Journal of Central South University 2012年第9期19卷 2548-2553页

作者： SON Young-ho lee sang-min Department of Electronic Engineering Inha University Institute for Information and Electronics Research Inha University

An improved speech absence probability estimation was proposed using environmental noise classification for speech enhancement.A relevant noise estimation approach,known as the speech presence uncertainty tracking method,requires seeking the "a priori" probability of speech absence that is derived by applying microphone input signal and the noise signal based on the estimated value of the "a posteriori" signal-to-noise ratio(SNR).To overcome this problem,first,the optimal values in terms of the perceived speech quality of a variety of noise types are ***,the estimated optimal values are assigned according to the determined noise type which is classified by a real-time noise classification algorithm based on the Gaussian mixture model(GMM).The proposed algorithm estimates the speech absence probability using a noise classification algorithm which is based on GMM to apply the optimal parameter of each noise type,unlike the conventional approach which uses a fixed threshold and smoothing *** performance of the proposed method was evaluated by objective tests,such as the perceptual evaluation of speech quality(PESQ) and composite *** was then evaluated by a subjective test,namely,mean opinion scores(MOS) under various noise *** proposed method show better results than existing methods.

关键词： speech enhancement soft decision speech absence probability Gaussian mixture model (GMM)

Weighted Forwarding in Graph Convolution Networks for Recommendation Information Systems

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Computers, Materials & Continua 2024年第2期78卷 1897-1914页

作者： sang-min lee Namgi Kim Department of Computer Science Kyonggi UniversitySuwonKorea

Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the *** Convolution Network(GCN)algorithms have been employed to implement the RIS ***,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning *** address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)*** proposed method involves multiplying the embedding results with different weights for each hop layer during graph *** applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding *** approach facilitates the learning of more hop layers within the GCN *** efficacy of the WF-GCN was demonstrated through its application to various *** the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,***,in the *** dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,***,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.

关键词： Deep learning graph neural network graph convolution network graph convolution network model learning method recommender information systems

Comparison of wrist motion classification methods using surface electromyogram

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Journal of Central South University 2013年第4期20卷 960-968页

作者： JEONG Eui-chul KIM Seo-jun SONG Young-rok lee sang-min Department of Electronic Engineering Inha University

The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.

关键词： Gaussian mixture model k-nearest neighbor quadratic discriminant analysis linear discriminant analysis electromyogram (EMG) pattern classification feature extraction

Recommendation application for video head impulse test based on fuzzy logic control

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Journal of Central South University 2016年第5期23卷 1208-1214页

作者： NGUYEN Thi Anh Dao KIM Dae Young lee sang min KIM Kyu Sung Seong Ro lee KWON Jang Woo Department of Computer and Information Engineering Inha University Department of Otorhinolaryngology Inha University Hospital Department of Electronic Engineering Inha University Department of Information and Electronics Engineering Mokpo National University

Vestibulo-ocular reflex(VOR) is an important biological reflex that controls eye movement to ensure clear vision while the head is in ***,VOR measurement is commonly done with a video head impulse test based on a velocity gain algorithm or a position gain algorithm,in which velocity gain is a VOR calculation on head and eye velocity,whereas position gain is calculated from head and eye *** aim of this work is first to compare the two algorithms' performance and to detect covert catch-up saccade,then to propose a stand-alone recommendation application for the patient's *** the first experiment,for ipsilesional and contralesional sides,the calculated position gain(0.94±0.17) is higher than velocity gain(0.84±0.19).Moreover,gain asymmetry of both lesion and intact sides using velocity gain is mostly higher than that from using position gain(four out of five subjects).Consequently,for subjects who have unilateral vestibular neuritis diagnosed from clinical symptoms and a vestibular function test,vestibular weakness is depicted by velocity gain much better than by position *** catch-up saccade and position gain then are used as inputs for recommendation applications.

关键词： vestibulo-ocular response video head impulse velocity gain position gain desaccade