• 대한음성학회지:말소리
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• 제63호
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• pp.101-112
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• 2007

Spoken dialog system development includes many laborious and inefficient tasks. Since there are many components such as speech recognition, language understanding, dialog management and knowledge management in a spoken dialog system, a developer should take an effort to edit corpus and train each model separately. To reduce a cost for editing corpus and training each model, we need more systematic and efficient working environment. For the working environment, we propose DialogStudio as a spoken dialog system workbench.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
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• pp.29-32
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• 2007

This paper describes a multimodal dialog system that uses Hidden Information State (HIS) method to manage the human-machine dialog. HIS dialog manager is a variation of classic partially observable Markov decision process (POMDP), which provides one of the stochastic dialog modeling frameworks. Because dialog modeling using conventional POMDP requires very large size of state space, it has been hard to apply POMDP to the real domain of dialog system. In HIS dialog manager, system groups the belief states to reduce the size of state space, so that HIS dialog manager can be used in real world domain of dialog system. We adapted this HIS method to Smart-home domain multimodal dialog system.

• 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.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
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• pp.311-314
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• 2007

Spoken dialog system development includes many laborious and inefficient tasks. Since there are many components such as speech recognizer, language understanding, dialog management and knowledge management in a spoken dialog system, a developer should take an effort to edit corpus and train each model separately. To reduce a cost for editting corpus and training each models, we need more systematic and efficent working environment. For the working environment, we propose DialogStudio as an spoken dialog system workbench.

• Journal of Computing Science and Engineering
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• 제4권1호
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• pp.1-22
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• 2010

A field of spoken dialog systems is a rapidly growing research area because the performance improvement of speech technologies motivates the possibility of building systems that a human can easily operate in order to access useful information via spoken languages. Among the components in a spoken dialog system, the dialog management plays major roles such as discourse analysis, database access, error handling, and system action prediction. This survey covers design issues and recent approaches to the dialog management techniques for modeling the dialogs. We also explain the user simulation techniques for automatic evaluation of spoken dialog systems.

• 한국철도학회논문집
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• 제14권2호
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• pp.130-136
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• 2011

본 논문에서는 철도예약서비스를 위한 SIP를 기반으로 하는 텔레포니 환경에서의 VoiceXML을 이용한 실시간 음성인식을 구현하는 방안을 제안하였다. 제안된 방법은 PSTN 또는 인터넷을 통하여 들어온 음성신호를 VoiceXML을 이용한 Dialog 처리를 하고 전송된 음성신호를 음성인식 시스템에서 처리하여 출력된 결과값을 VoiceXML의 Dialog에 반환하여 사용자에게 전달하는 방식이다. VASR 시스템은 Dialog를 처리하는 Dialog 서버, 음성신호를 처리하기 위한 APP서버, 그리고 음성인식을 처리하는 음성인식 시스템으로 구성된다. 본 논문에서는 텔레포니 환경에서의 음성신호 처리를 위하여 VoiceXML의 Record Tag 기능을 이용하여 음성신호를 녹음하고 이를 실시간 재생하여 음성인식 시스템으로 전송하는 방식을 구현하였다.

• 대한음성학회지:말소리
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• 제53호
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• pp.171-183
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• 2005

Call Control eXtensible Markup (CCXML) is a standard language that supports a call control of voice dialog systems such as VoiceXML based systems. CCXML allows developers to handle telephony calls in an easy way without deep knowledge about telephony networks and their switching systems.We design and implement a call control markup interpreter. At the implementation, we use a Dialogic JCT-LS board, but, by designing a wrapping class for CTI (computer telephony board) features, the interpreter can easily adopt other CTI boards. We also design and implement event-based interaction scheme between the interpreter and voice dialog systems. For verifying the interaction scheme, we implement a simple voice dialog system.

• 융합정보논문지
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• 제9권8호
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• pp.1-8
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• 2019

대화시스템은 인간과 컴퓨터의 상호작용에 새로운 패러다임이 되고 있다. 자연어로써 상호작용함으로써 인간은 보다 자연스럽고 편리하게 각종 서비스를 누릴 수 있게 되었다. 대화시스템의 구조는 일반적으로 음성 인식, 자연어 이해, 문맥 파악 등의 여러 모듈의 파이프라인으로 이뤄지는데, 본 연구에서는 자연어 이해 모듈의 도메인 분류 문제를 풀기 위해 convolutional neural network, random forest 등의 기계학습 모델을 비교하였다. 사람이 직접 태깅한 총 7개 서비스 도메인 데이터에 대하여 각 문장의 도메인을 분류하는 실험을 수행하였고 random forest 모델이 F1 score 0.97 이상으로 가장 높은 성능을 달성한 것을 보였다. 향후 다른 기계학습 모델들을 추가 실험함으로써 도메인 분류 성능 개선을 지속할 계획이다.

• 한국컴퓨터정보학회논문지
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• 제23권1호
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• pp.17-24
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• 2018

With improvement of speech recognition and natural language processing, dialog systems are recently adapted to various service domains. It became possible to get desirable services by conversation through the dialog system, but it is still necessary to improve separate modules, such as domain detection, intention detection, named entity recognition, and out-of-domain detection, in order to achieve stable service offer. When it misclassifies an in-domain sentence of conversation as out-of-domain, it will result in poor customer satisfaction and finally lost business. As there have been relatively small number of studies related to the out-of-domain detection, in this paper, we introduce a new method using a hierarchical Dirichlet process and demonstrate the effectiveness of it by experimental results on Korean dataset.

• 한국지능시스템학회논문지
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• 제15권2호
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• pp.173-178
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• 2005

본 논문은 보다 편리한 가정 생활환경 구축을 목적으로 한 가상대화시스템 구현에 관한 연구이다. 이를 실현하기 위하여 본 논문은 음성인식, 음성합성, 비디오 신호 및 센서신호처리 등의 멀티미디어 신호처리에 그 기술적 기반을 두고 있다. 대화시스템의 중요한 모듈로서의 음성합성기, HM-Net(Hidden Markov Network)에 기반한 실시간 음성인식기, 픽셀의 밝기차를 이용한 실시간 움직임 검출 및 터치센서 등을 대화시스템에 통합함으로써 이루어진다. 실제 구동 실험에서 주위 노이즈 환경의 영향으로 시뮬레이션 결과보다는 성능이 떨어지나, 소파에 앉아있는 동안 자동되는 시스템의 실험 평가에서 가전제품 능의 컨트롤이 비교적 사용하기 쉬웠다는 결과를 얻었다.