• Title/Summary/Keyword: DIALOG

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DialogStudio: A Spoken Dialog System Workbench (음성대화시스템 워크벤취로서의 DialogStudio 개발)

  • Jung, Sang-Keun;Lee, Cheong-Jae;Lee, Gary Geun-Bae
    • MALSORI
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    • no.63
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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.

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Multimodal Dialog System Using Hidden Information State Dialog Manager (Hidden Information State 대화 관리자를 이용한 멀티모달 대화시스템)

  • Kim, Kyung-Duk;Lee, Geun-Bae
    • Proceedings of the KSPS conference
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    • 2007.05a
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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.

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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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    • v.2 no.1
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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.

Recent Approaches to Dialog Management for Spoken Dialog Systems

  • Lee, Cheong-Jae;Jung, Sang-Keun;Kim, Kyung-Duk;Lee, Dong-Hyeon;Lee, Gary Geun-Bae
    • Journal of Computing Science and Engineering
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    • v.4 no.1
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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.

Study on Method Constructing Dialog Act Tagged Corpus for Dialog System in Car (차량용 대화 시스템을 위한 Dialog Act 태깅 코퍼스 구축 방법 연구)

  • Choi, Sung-Kwon;Kwon, Oh-Woog;Kim, Young-Gil
    • Annual Conference on Human and Language Technology
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    • 2012.10a
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    • pp.181-184
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    • 2012
  • 본 논문에서는 한국전자통신연구원 언어처리연구팀에서 개발하고 있는 차량용 대화 시스템을 위한 Dialog Act 태깅 코퍼스 구축 방법에 대해 기술하는 것을 목표로 한다. 차량용 태깅 코퍼스 구축 방법은 크게 차량용 대화 코퍼스 수집과 수집된 대화 코퍼스에 Dialog Act를 반자동으로 태깅하는 방법으로 나눌 수 있다. 차량용 대화 코퍼스 수집은 1) 대화플랜 맵 구축, 2) 표준대화 구축, 3) 자유대화 구축, 4) 사용자 발화에 패러프래징 발화 구축의 순으로 구축되었다. Dialog Act 태깅은 수집된 대화코퍼스로부터 슬롯 후보를 추출하여 슬롯 체계를 구축한 후 반자동 슬롯 태깅을 실시하고, 슬롯 태깅 결과와 Dialog Act Type을 조합하여 Dialog Act 태깅 코퍼스를 구축하였다. 이렇게 구축된 Dialog Act 태깅 코퍼스는 차량 공조시스템(에어컨, 히터 등) 및 차량 응급 조치 정보 서비스와 같은 차량용 대화 시스템에 적용 중에 있다.

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DialogStudio;A Spoken Dialog System Workbench (음성대화시스템 워크벤취로서의 DialogStudio 개발)

  • Jung, Sang-Keun;Lee, Cheon-Jae;Lee, Geun-Bae
    • Proceedings of the KSPS conference
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    • 2007.05a
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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.

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Robust Dialog Management with N-best Hypotheses Using Dialog Examples and Agenda (대화 예제와 아젠다를 이용한 음성 인식 오류에 강인한 대화 관리 방법)

  • Lee, Cheongjae;Jung, Sangkeun;Kim, Kyungduk;Lee, Gary Geunbae
    • Annual Conference on Human and Language Technology
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    • 2008.10a
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    • pp.156-161
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    • 2008
  • This work presents an agenda-based approach to improve the robustness of the dialog manager by using dialog examples and n-best recognition hypotheses. This approach supports n-best hypotheses in the dialog manager and keeps track of the dialog state using a discourse interpretation algorithm with the agenda graph and focus stack. Given the agenda graph and n-best hypotheses, the system can predict the next system actions to maximize multi-level score functions. To evaluate the proposed method, a spoken dialog system for a building guidance robot was developed. Preliminary evaluation shows this approach would be effective to improve the robustness of example-based dialog modeling.

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A Study on Realization of Speech Recognition System based on VoiceXML for Railroad Reservation Service (철도예약서비스를 위한 VoiceXML 기반의 음성인식 구현에 관한 연구)

  • Kim, Beom-Seung;Kim, Soon-Hyob
    • Journal of the Korean Society for Railway
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    • v.14 no.2
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    • pp.130-136
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    • 2011
  • This paper suggests realization method for real-time speech recognition using VoiceXML in telephony environment based on SIP for Railroad Reservation Service. In this method, voice signal incoming through PSTN or Internet is treated as dialog using VoiceXML and the transferred voice signal is processed by Speech Recognition System, and the output is returned to dialog of VoiceXML which is transferred to users. VASR system is constituted of dialog server which processes dialog, APP server for processing voice signal, and Speech Recognition System to process speech recognition. This realizes transfer method to Speech Recognition System in which voice signal is recorded using Record Tag function of VoiceXML to process voice signal in telephony environment and it is played in real time.

Internet Database Retrieval Efficiency vs. DIALOG Retrieval Efficiency (DIALOG와 인터넷 데이터베이스의 검색 효율성에 관한 비교 연구)

  • Kim, Hyun-Hee;Choi, Chang-Seok;Ahn, Tae-Kyoung;Shin, Myoung-Cho
    • Journal of the Korean Society for information Management
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    • v.17 no.1
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    • pp.103-127
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    • 2000
  • This study compared finding economic and energy information on the WWW to finding the same information on DIALOG, a traditional search service. Professional searchers answered 20 questions for end users using either of DIALOG and one Internet database (general search engine or Web database). The relevance of the results in both sets of answers was ranked by searchers and end-users, respectively. The study found that searching for information on the Web took at least twice as long as it did when using DIALOG. Relevance rating was a little higher for materials found on DIALOG. However, the relevance rating difference between two systems was not so higher than we expected. From the research results, we conclude that Internet database including Web database and general search engines is providing valuable information of economic and energy subject areas.

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