• 제목/요약/키워드: Semantic recognition

검색결과 194건 처리시간 0.024초

센서융합을 통한 시맨틱 지도의 작성 (Sensor Fusion-Based Semantic Map Building)

  • 박중태;송재복
    • 제어로봇시스템학회논문지
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    • 제17권3호
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    • pp.277-282
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    • 2011
  • This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

신택틱 패턴 인식 알고리즘에 의한 심전도 신호의 패턴 분류에 관한 연구 (A Study of ECG Pattern Classification of Using Syntactic Pattern Recognition)

  • 남승우;이명호
    • 대한의용생체공학회:의공학회지
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    • 제12권4호
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    • pp.267-276
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    • 1991
  • This paper describes syntactic pattern recognition algorithm for pattern recognition and diagnostic parameter extraction of ECG signal. ECG signal which is represented linguistic string is evaluated by pattern grammar and its interpreter-LALR(1) parser for pattern recognition. The proposed pattern grammar performs syntactic analysis and semantic evaluation simultaneously. The performance of proposed algorithm has been evaluated using CSE database.

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Using Utterance and Semantic Level Confidence for Interactive Spoken Dialog Clarification

  • Jung, Sang-Keun;Lee, Cheong-Jae;Lee, Gary Geunbae
    • Journal of Computing Science and Engineering
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    • 제2권1호
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    • pp.1-25
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    • 2008
  • Spoken dialog tasks incur many errors including speech recognition errors, understanding errors, and even dialog management errors. These errors create a big gap between the user's intention and the system's understanding, which eventually results in a misinterpretation. To fill in the gap, people in human-to-human dialogs try to clarify the major causes of the misunderstanding to selectively correct them. This paper presents a method of clarification techniques to human-to-machine spoken dialog systems. We viewed the clarification dialog as a two-step problem-Belief confirmation and Clarification strategy establishment. To confirm the belief, we organized the clarification process into three systematic phases. In the belief confirmation phase, we consider the overall dialog system's processes including speech recognition, language understanding and semantic slot and value pairs for clarification dialog management. A clarification expert is developed for establishing clarification dialog strategy. In addition, we proposed a new design of plugging clarification dialog module in a given expert based dialog system. The experiment results demonstrate that the error verifiers effectively catch the word and utterance-level semantic errors and the clarification experts actually increase the dialog success rate and the dialog efficiency.

Using Syntax and Shallow Semantic Analysis for Vietnamese Question Generation

  • Phuoc Tran;Duy Khanh Nguyen;Tram Tran;Bay Vo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권10호
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    • pp.2718-2731
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    • 2023
  • This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.

미등록어의 의미 범주 분석을 이용한 복합명사 분해 (Segmentation of Korean Compound Nouns Using Semantic Category Analysis of Unregistered Nouns)

  • 강유환;서영훈
    • Journal of Information Technology Applications and Management
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    • 제11권4호
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    • pp.95-102
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    • 2004
  • This paper proposes a method of segmenting compound nouns which include unregistered nouns into a correct combination of unit nouns using characteristics of person's names, loanwords, and location names. Korean person's name is generally composed of 3 syllables, only relatively small number of syllables is used as last names, and the second and the third syllables combination is somewhat restrictive. Also many person's names appear with clue words in compound nouns. Most loanwords have one or more syllables which cannot appear in Korean words, or have sequences of syllables different from usual Korean words. Location names are generally used with clue words designating districts in compound nouns. Use of above characteristics to analyze compound nouns not only makes segmentation more accurate, helps natural language systems use semantic categories of those unregistered nouns. Experimental results show that the precision of our method is approximately 98% on average. The precision of human names and loanwords recognition is about 94% and about 92% respectively.

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동해연안의 주택경관 유형별 인지 평가에 관한 연구 (A Study on evaluation of recognition with type of Housing landscape in Donghae Seaside)

  • 조원석;김흥기;김용기;신정섭
    • 한국농촌건축학회논문집
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    • 제8권1호
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    • pp.80-89
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    • 2006
  • This study is derived from relation between the natural landscape and architectural landscape. The type of landscape in Donghae seaside consist of three; Road, Mountain, Seaside. And we selected three landscapes about individual housing; Western, Traditional, Modern. This paper is analyzed 18-simulation scenes, which evaluated with semantic differential method in using 12-bipolar adjectives. The results of this study are as follows(ref: table 6). 1)The housing of western style do not correspond with landscape of Road, but landscape of mountain and seaside were suitable to the western style. 2)Mountain in Donghae seaside harmonizes with housing of traditional style. 3)Even though the housing of modern style were marked low assessment in three landscape, we found out relation, modern housing was well-matched with load landscape.

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Automatic Detection of Korean Accentual Phrase Boundaries

  • Lee, Ki-Yeong;Song, Min-Suck
    • The Journal of the Acoustical Society of Korea
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    • 제18권1E호
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    • pp.27-31
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    • 1999
  • Recent linguistic researches have brought into focus the relations between prosodic structures and syntactic, semantic or phonological structures. Most of them prove that prosodic information is available for understanding syntactic, semantic and discourse structures. But this result has not been integrated yet into recent Korean speech recognition or understanding systems. This study, as a part of integrating prosodic information into the speech recognition system, proposes an automatic detection technique of Korean accentual phrase boundaries by using one-stage DP, and the normalized pitch pattern. For making the normalized pitch pattern, this study proposes a method of modified normalization for Korean spoken language. For the experiment, this study employs 192 sentential speech data of 12 men's voice spoken in standard Korean, in which 720 accentual phrases are included, and 74.4% of the accentual phrase boundaries are correctly detected while 14.7% are the false detection rate.

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심전도 신호의 신택틱 패턴인식 (Syntatic Pattern recognition of the ECG)

  • 남승우;이병채;신건수;이재준;이명호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1991년도 추계학술대회
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    • pp.129-132
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    • 1991
  • This paper describes the ECG pattern recognition using the syntatic pattern recognition algorithm. The algorithm uses the BNF rule wi th the semantic evaluation which has the structural Information of the ECG. This algorithm is constructed with (1) removing the baseline drift by the Cubic spline function and exract the significant point by the line-approximation algorithm, (2) syntatic peak recognition algorithm with the extracted significant point, (3) produce the token which is used pattern recognition, (4) pattern recognition of the ECG by the syntatic pattern recognition algorithm, (5) extract the parameter with the pattern recognized ECG signal.

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Bird's Eye View Semantic Segmentation based on Improved Transformer for Automatic Annotation

  • Tianjiao Liang;Weiguo Pan;Hong Bao;Xinyue Fan;Han Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권8호
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    • pp.1996-2015
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    • 2023
  • High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

BiLSTM 모델과 형태소 자질을 이용한 서술어 인식 방법 (Predicate Recognition Method using BiLSTM Model and Morpheme Features)

  • 남충현;장경식
    • 한국정보통신학회논문지
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    • 제26권1호
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    • pp.24-29
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    • 2022
  • 정보 추출 및 질의응답 시스템 등 다양한 자연어 처리 분야에서 사용되는 의미역 결정은 주어진 문장과 서술어에 대해 서술어와 연관성 있는 논항들의 관계를 파악하는 작업이다. 입력으로 사용되는 서술어는 형태소 분석과 같은 어휘적 분석 결과를 이용하여 추출하지만, 한국어 특성상 문장의 의미에 따라 다양한 패턴을 가질 수 있기 때문에 모든 언어학적 패턴을 만들 수 없다는 문제점이 있다. 본 논문에서는 사전에 언어학적 패턴을 정의하지 않고 신경망 모델과 사전 학습된 임베딩 모델 및 형태소 자질을 추가한 한국어 서술어를 인식하는 방법을 제안한다. 실험은 모델의 변경 가능한 파라미터에 대한 성능 비교, 임베딩 모델과 형태소 자질의 사용 유무에 따른 성능 비교를 하였으며, 그 결과 제안한 신경망 모델이 92.63%의 성능을 보였음을 확인하였다.