음성인식기를 이용한 한국인의 외국어 발화오류 자동 검출

권철홍,강효원,이상필,Kwon Chul-Hong,Kang Hyo-Won,Lee Sang-Pil 대한음성학회 2003 말소리 Vol.48 No.-

An automatic pronunciation correction system provides learners with correction guidelines for each mispronunciation. In this paper we propose an HMM based speech recognizer which automatically classifies pronunciation errors when Korean speak Japanese. For this purpose we also develop phoneme recognizers for Korean and Japanese. Experimental results show that the machine scores of the proposed recognizer correlate with expert ratings well.

열악한 환경에 강인한 화자인증을 위한 위상 기반 특징 추출 기법

권철홍,Kwon, Chul-Hong 한국정보통신학회 2010 한국정보통신학회논문지 Vol.14 No.3

Additive noise and channel distortion strongly degrade the performance of speaker verification systems, as it introduces distortion of the features of speech. This distortion causes a mismatch between the training and recognition conditions such that acoustic models trained with clean speech do not model noisy and channel distorted speech accurately. This paper presents a phase-related feature extraction method in order to improve the robustness of the speaker verification systems. The instantaneous frequency is computed from the phase of speech signals and features from the histogram of the instantaneous frequency are obtained. Experimental results show that the proposed technique offers significant improvements over the standard techniques in both clean and adverse testing environments. 화자인증 시스템은 훈련 환경과 인식 환경이 다른 경우 인식 성능이 크게 저하된다. 이러한 훈련과 인식 환경의 불일치는 다양한 잡음과 상이한 채널 환경 때문이다. 본 논문은 화자인증 시스템의 강인성 개선을 위하여 음성신호의 위상에 기반한 특정 추출 기법을 제안한다. 이 방법은 음성신호의 위상으로부터 순시 주파수를 계산하여 대역별로 순시 주파수를 모두 모아 구한 히스토그램으로부터 특징 계수를 추출한다. 이 특징 파라미터를 적용한 결과 조 용한 환경뿐만 아니라 잡음환경 그리고 채널 왜곡 환경에서도 화자인증 시스템의 성능이 개선됨을 알 수 있다.

히스토그램 변환에서 기준분포의 표준편차 변경에 따른 강인한 화자인증 성능 개선

권철홍(Kwon Chul Hong) 한국음성학회 2010 말소리와 음성과학 Vol.2 No.3

Additive noise and channel mismatch strongly degrade the performance of speaker verification systems, as they distort the features of speech. In this paper a histogram transformation technique is presented to improve the robustness of text-independent speaker verification systems. The technique transforms the features extracted from speech such that theirhistogram is conformed to a reference distribution. The effect of different standard deviations for the reference distribution is investigated. Experimental results indicate that, in channel mismatched environments, the proposed technique offers significant improvements over existing techniques. We also verify performance improvement of the proposed method using statistics.

단순작업으로 인한 정신피로도 측정을 위한 음성기술을 이용한 CART 기반 진단모델

권철홍(Kwon, Chul Hong) 한국음성학회 2016 말소리와 음성과학 Vol.8 No.4

This paper presents a CART(Classification and Regression Tree)-based model to diagnose mental fatigue using speech technology. The parameters used in the model are the significant speech parameters highly correlated to the fatigue and questionnaire responses obtained before and after imposing the fatigue. It is shown from the experiments that the proposed model achieves classification accuracies of 96.67% and 98.33% using the speech parameters and questionnaire responses, respectively. This implies that the proposed model can be used as a tool to diagnose the mental fatigue, and that speech technology is useful to diagnose the fatigue.

돼지의 빠른 자세 결정과 머리 제거를 위한영상처리 및 딥러닝 기법

안한세,최원석,박선화,정용화,박대희 한국정보처리학회 2019 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.8 No.11

The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig’s weight is an important issue in productivity perspective. In order to estimate the pig’s weight by using the number of pig’s pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig’s posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig’s head by using light weighted image processing technique. First, we determine the pig’s posture by comparing the length from the center of the pig‘s body to the outline of the pig in the binary image. Then, we train the location of pig’s head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig’s head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig’s head. In the Experiment result, we confirmed that the pig’s posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig’s head was removed with an accuracy of 0.96 and a processing speed of 48.97fps. 양돈 업계에서 돼지의 무게는 돼지의 건강이나 성장 상태, 출하 여부, 사육 환경, 사료 배급을 결정하는 주요 요인 중 하나이며, 따라서 돼지의 무게를 측정하는 것은 돼지의 생산성 측면에서 중요한 문제이다. Top-view 카메라에서 획득한 영상으로부터 돼지의 픽셀 수를 이용하여 돼지의 무게를 추정하고자 할 때, 정확한 픽셀 수 측정에 영향을 주는 돼지의 자세를 결정할 필요가 있으며, 픽셀 수 측정에 영향을 주는 머리 부분을 제거할 필요가 있다. 본 논문에서는 빠른 영상처리 기법을 이용하여 돼지의 자세를 빠르게 결정하고, 딥러닝 기반의 빠른 객체탐지 기법인 YOLO를 이용하여 돼지 머리 위치를 파악한 후, 경량화된 영상처리 기법을 이용하여 돼지의 머리와 몸통 경계를 획득하고 머리를 제거하는 방법을 제안한다. 즉, 빠른 영상처리 기법으로 이진화된 돼지의 영상 데이터에서 돼지의 몸통 중심점으로부터 돼지의 외곽선까지의 길이를 비교하여 돼지의 자세를 결정한다. 또한, 돼지의 머리 위치를 탐지하기 위하여 YOLO를 이용하여 영상 데이터 내의 돼지의 머리, 몸통, 엉덩이의 위치를 학습시킨 후, 곧은 자세의 돼지 머리 위치를 획득하고 머리 바깥 영역을 제거한다. 마지막으로 Convex-hull을 이용하여 돼지의 머리와 몸통 경계를 추정한 후, 머리를 제거한다. 실험 결과, 0.98의 정확도와 250.00fps의 수행속도로 돼지의 자세를 결정하였으며, 0.96의 정확도와 48.97fps의 수행속도로 돼지의 머리탐지 및 제거가 가능함을 확인하였다.

목소리 특성의 청취 평가에 기초한 사상체질과 음성 특징의 상관관계 분석

권철홍(Kwon, Chulhong),김종열(Kim, Jongyeol),김근호(Kim, Keunho),장준수(Jang, Junsu) 한국음성학회 2012 말소리와 음성과학 Vol.4 No.4

Sasang constitution experts utilize voice characteristics as an auxiliary measure for deciding a person"s constitutional group. This study aims at establishing a relationship between speech features and the constitutional groups by subjective listening evaluation of voice characteristics. A speech database of 841 speakers whose constitutional groups have been already diagnosed by Sasang constitution experts was constructed. Speech features related to speech source and vocal tract filter were extracted from five vowels and one sentence. Statistically significant speech features for classifying the groups were analyzed using SPSS. The features contributed to constitution classification were speaking rate, Energy, A1, A2, A3, H1, H2, H4, CPP for males in their 20s, F0_mean, CPP, SPI, HNR, Shimmer, Energy, A1, A2, A3, H1, H2, H4 for females in their 20s, Energy, A1, A2, A3, H1, H2, H4, CPP for male in the 60s, and Jitter, HNR, CPP, SPI for females in their 60s. Experimental results show that speech technology is useful in classifying constitutional groups.

경상북도 동해안 에너지클러스터 개선 추진 방향 연구

권철홍(Chul-Hong Kwon),전동협(Dong Hyup Jeon) 한국에너지기후변화학회 2019 한국에너지기후변화학회 학술대회 Vol.2019 No.11

[論文] 韓國型 市街地 走行 Mode의 開發硏究

권철홍(Chul hong Kwon),박선(Sun Park) 한국자동차공학회 1987 오토저널 Vol.9 No.1

<br/> The driving pattern was studied in Seoul along nineteen representative routes using a test car equipped with all the instruments required for recording traffic flow and measuring fuel consumption. Speed histories, gear shift points, instantaneous fuel consumption rates, etc. were recorded and the data were anlyzed to determine the traffic characteristics for Seoul.<br/> The Seoul-14 Mode has been developed to simulated actual driving conditions in Seoul with respect to fuel consumption. The average speed of the Seoul-14 Mode is 30.1 Km/h and the Mode length is 11.94 Km.

[解說] 수송부문의 Green Round 충격과 에너지절약 대책

권철홍(C.H.Kwon) 한국자동차공학회 1994 오토저널 Vol.16 No.2

사상체질과 음성특징과의 상관관계 연구

권철홍 ( Chul Hong Kwon ),김종열 ( Jong Yeol Kim ),김근호 ( Keun Ho Kim ),한성만 ( Sung Man Han ) 대전대학교 한의학연구소 2011 한의학연구소 논문집 Vol.19 No.2

Objective: Sasang constitution medicine utilizes voice characteristics to diagnose a person`s constitution. In this paper we propose methods to analyze Sasang constitution using speech information technology. That is, this study aims at establishing the relationship between Sasang constitutions and their corresponding voice characteristics by investigating various speech variables. Materials & Methods: Voice recordings of 1,406 speakers are obtained whose constitutions have been already diagnosed by the experts in the fields. A total of 144 speech features obtained from five vowels and a sentence are used. The features include pitch, intensity, formant, bandwidth, MDVP and MFCC related variables for each constitution. We analyze the speech variables and find whether there are statistically significant differences among three constitutions. Results: The main speech variables classifying three constitutions are related to pitch and MFCCs for male, and formant and MFCCs for female. The correct decision rate is 73.7% for male Soeumin, 63.3% for male Soyangin, 57.3% for male Taeumin, 74.0% for female Soeumin, 75.6% for female Soyangin, 94.3% for female Taeumin, and 73.0% on the average. Conclusion: Experimental results show that statistically significant correlation between some speech variables and the constitutions is observed.