• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.347-350
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• 한국컴퓨터정보학회논문지
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• 제14권10호
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• pp.217-223
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• 2009

모바일 단말기의 어휘 인식 시스템에서는 통계적 방법에 의한 어휘인식을 수행하고 N-gram을 이용한 통계적 문법 인식 시스템을 사용한다. 인식 대상이 되는 어휘의 수가 증가하면 어휘 인식 알고리즘이 복잡해지고 대규모의 탐색공간을 필요로 하게 되며 처리시간이 길어지므로 제한된 연산처리 능력과 메모리로는 처리하기가 불가능하다. 따라서 본 논문에서는 이러한 단점을 개선하고 어휘 인식을 최적화하기 위하여 MLHF 시스템을 제안한다. MLHF는 FLaVoR의 구조를 이용하여 음향학적 탐색과 언어적 탐색을 분리하여 음향학적 탐색에서는 HMM을 사용하고 언어적 탐색 단계에서는 Levenshtein distance 알고리즘을 사용한다. 시스템 성능 평가 결과 어휘 종속 인식률은 98.63%, 어휘 독립 인식률은 97.91%의 인식률을 나타냈으며 인식속도는 1.61초로 나타내었다.

• International Journal of Advanced Culture Technology
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• 제7권3호
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• pp.134-142
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• 2019

As the 4th industry has been widely distributed, there is a need for a process of real-time image recognition in various fields such as identification of company employees, security maintenance, and development of military weapons. Therefore, in this paper, we will propose an algorithm that effectively recognizes a test object by comparing it with the DB model. The proposed object recognition system first expresses the outline of the test object as a set of vertices with the distances of predefined length or more. Then, the degree of matching of the structures of the two objects is calculated by examining the distances to the outline of the DB model from the vertices constituting the test object. Because the proposed recognition algorithm uses the outline of the object, the recognition process is easy to understand, simple to implement, and a satisfactory recognition result is obtained.

• ETRI Journal
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• 제46권1호
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• pp.71-81
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• 2024

Recent advances in deep learning for speech and visual recognition have accelerated the development of multimodal speech recognition, yielding many innovative results. We introduce a Korean audiovisual speech recognition corpus. This dataset comprises approximately 150 h of manually transcribed and annotated audiovisual data supplemented with additional 2000 h of untranscribed videos collected from YouTube under the Creative Commons License. The dataset is intended to be freely accessible for unrestricted research purposes. Along with the corpus, we propose an open-source framework for automatic speech recognition (ASR) and audiovisual speech recognition (AVSR). We validate the effectiveness of the corpus with evaluations using state-of-the-art ASR and AVSR techniques, capitalizing on both pretrained models and fine-tuning processes. After fine-tuning, ASR and AVSR achieve character error rates of 11.1% and 18.9%, respectively. This error difference highlights the need for improvement in AVSR techniques. We expect that our corpus will be an instrumental resource to support improvements in AVSR.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1473-1480
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• 2018

The extraction and recognition of human motion characteristics need to combine biometrics to determine and judge human behavior in the movement and distinguish individual identities. The so-called biometric technology, the specific operation is the use of the body's inherent biological characteristics of individual identity authentication, the most noteworthy feature is the invariance and uniqueness. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. And we will use the KTH database to train and test the recognition system. Experiments have been very desirable results.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2005년도 춘계 학술대회 발표논문집
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• pp.99-102
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• 2005

Research efforts have been made for out-of-vocabulary word rejection to improve the confidence of speech recognition systems. However, little attention has been paid to non-recognition sentence rejection. According to the appearance of pronunciation correction systems using speech recognition technology, it is needed to reject non-recognition sentences to provide users with more accurate and robust results. In this paper, we introduce standard phoneme based sentence rejection system with no need of special filler models. Instead we used word spotting ratio to determine whether input sentences would be accepted or rejected. Experimental results show that we can achieve comparable performance using only standard phoneme based recognition network in terms of the average of FRR and FAR.

• 대한음성학회지:말소리
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• 제50호
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• pp.71-83
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• 2004

Recently, broadcast news speech recognition has become one of the most attractive research areas. If we can transcribe automatically the broadcast news and store their contents in the text form instead of the video or audio signal itself, it will be much easier for us to search for the multimedia databases to obtain what we need. However, the desirable speech signal in the broadcast news are usually affected by the interfering signals such as the background noise and/or the music. Also, the speech of the reporter who is speaking over the telephone or with the ill-conditioned microphone is severely distorted by the channel effect. The interfered or distorted speech may be the main reason for the poor performance in the broadcast news speech recognition. In this paper, we investigated some methods to cope with the problems and we could see some performance improvements in the noisy broadcast news speech recognition.

• 동서간호학연구지
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• 제17권1호
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• pp.9-15
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• 2011

Purpose: The purpose of this study was to investigate recognition and knowledge regarding clinical trials, in particular, after a clinical trial education program (CTEP) among student nurses. Methods: A cross-sectional survey design of 215 student nurses at a university in Seoul was used with structured questionnaires. Results: Respondents had a high level of need for clinical trial and moderate levels in favorable image, safety, and need for education regarding clinical trial. The respondents who had participated in the CTEP felt the clinical trial more favorable and safer than those who did not. However, there were no significant differences in necessity of clinical trials and need for education regarding clinical trial between the CTEP participation and no participation groups. Respondents had a high level of knowledge about clinical trial, even though half of the respondents misunderstood that the physician can convince the subject to participate in clinical trial. There was no significant difference in knowledge level between groups. One third of the respondents had an intention to work in the area related to clinical trial because of aptitude or future prospect. Conclusion: The results of this study demonstrated that the CTEP might have an effect on student nurses' recognition rather than knowledge. The CTEP should be therefore developed targeting specific areas of misconceptions and recognition changes.

• 한국정보통신학회논문지
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• 제8권7호
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• pp.1480-1487
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• 2004

본 연구에서는 원격 카메라 로봇 제어를 위한 새로운 제스처 인식 방법을 제안하였다. 제스처 인식의 전처리 단계인 동적 제스처의 세그먼테이션이며, 이를 위한 기존의 방법은 인식 대상에 대한 많은 칼라정보를 필요로 하고, 인식단계에서는 각각 제스처에 대한 많은 특징벡터들을 요구하는 단점이 있다. 이러한 단점을 개선하기 위해, 본 연구에서는 동적 제스처의 세그먼테이션을 위한 새로운 Max-Min 탐색법과 제스처 특징 추출을 위한 평균 공간 사상법과 무게중심법, 그리고 인식을 위한 다층 퍼셉트론 신경망의 구조 둥을 제안하였다 실험에서 제안된 기법의 인식율이 90%이상으로 나타났으며, 이 결과는 원격 로봇 제어를 위한 휴먼컴퓨터 인터페이스(HCI : Human Compute. Interface)장치로 사용 가능함을 보였다.

• The Journal of Korean Physical Therapy
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• 제23권2호
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• pp.77-84
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• 2011

Purpose: This study was designed to investigate the level of recognition and utilization of Korean physical therapists for assistive technology. Methods: The subjects of this study were 218 physical therapists who worked in various institutions in Seoul, Kyonggi-do, and Choongchung area. A questionnaire was developed using a related article. Simple descriptive statistics were used for respondent characteristics, and for the level of recognition and utilization. Results: The physical therapists reported having a less-than-average level of recognition and utilization for assistive technology. They were cognizant that the use of assistive technology devices were used mainly for specific outcome such as mobility, seating and position, and ADL. Conclusion: Our findings indicate that physical therapists need more opportunities for training in assistive technology. For effective clinical applications of assistive technology, there should be continuous support, such as college education, continued education, and related seminars.