000 07334nam a2200553 i 4500
001 8042134
003 IEEE
005 20220712211818.0
006 m o d
007 cr |n|||||||||
008 171024s2015 maua ob 001 eng d
010 _z 2010051228 (print)
020 _a9781119992691
_qelectronic
020 _z9780470688243
_qhardback
024 7 _a10.1002/9781119992691
_2doi
035 _a(CaBNVSL)mat08042134
035 _a(IDAMS)0b00006485f11a11
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aP95.3
_b.S665 2011eb
082 0 0 _a006.4/54
_222
245 0 0 _aSpoken language understanding :
_bsystems for extracting semantic information from speech /
_c[editors] Gokhan Tur, Renato De Mori.
264 1 _aHoboken, New Jersey :
_bWiley,
_c2011.
264 2 _a[Piscataqay, New Jersey] :
_bIEEE Xplore,
_c[2011]
300 _a1 PDF (xxx, 450 pages:) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aList of Contributors -- Forward -- Preface -- 1 Introduction (Gokhan Tur and Renato De Mori) -- 1.1 A Brief History of Spoken Language Understanding -- 1.2 Organization of the Book -- PART 1 SPOKEN LANGUAGE UNDERSTANDING FOR HUMAN/MACHINE INTERACTIONS -- 2 History of Knowledge and Processes for Spoken Language Understanding (Renato De Mori) -- 2.1 Introduction -- 2.2 Meaning Representation and Sentence Interpretation -- 2.3 Knowledge Fragments and Semantic Composition -- 2.4 Probabilistic Interpretation in SLU Systems -- 2.5 Interpretation with Partial Syntactic Analysis -- 2.6 Classification Models for Interpretation -- 2.7 Advanced Methods and Resources for Semantic Modeling and Interpretation -- 2.8 Recent Systems -- 2.9 Conclusions -- References -- 3 Semantic Frame-based Spoken Language Understanding (Ye-Yi Wang, Li Deng and Alex Acero) -- 3.1 Background -- 3.2 Knowledge-based Solutions -- 3.3 Data-driven Approaches -- 3.4 Summary -- References -- 4 Intent Determination and Spoken Utterance Classification (Gokhan Tur and Li Deng) -- 4.1 Background -- 4.2 Task Description -- 4.3 Technical Challenges -- 4.4 Benchmark Data Sets -- 4.5 Evaluation Metrics -- 4.6 Technical Approaches -- 4.7 Discussion and Conclusions -- References -- 5 Voice Search (Ye-Yi Wang, Dong Yu, Yun-Cheng Ju and Alex Acero) -- 5.1 Background -- 5.2 Technology Review -- 5.3 Summary -- References -- 6 Spoken Question Answering (Sophie Rosset, Olivier Galibert and Lori Lamel) -- 6.1 Introduction -- 6.2 Specific Aspects of Handling Speech in QA Systems -- 6.3 QA Evaluation Campaigns -- 6.4 Question-answering Systems -- 6.5 Projects Integrating Spoken Requests and Question Answering -- 6.6 Conclusions -- References -- 7 SLU in Commercial and Research Spoken Dialogue Systems (David Suendermann and Roberto Pieraccini) -- 7.1 Why Spoken Dialogue Systems (Do Not) Have to Understand -- 7.2 Approaches to SLU for Dialogue Systems -- 7.3 From Call Flow to POMDP: How Dialogue Management Integrates with SLU.
505 8 _a7.4 Benchmark Projects and Data Sets -- 7.5 Time is Money: The Relationship between SLU and Overall Dialogue System Performance -- 7.6 Conclusion -- References -- 8 Active Learning (Dilek Hakkani-T�ur and Giuseppe Riccardi) -- 8.1 Introduction -- 8.2 Motivation -- 8.3 Learning Architectures -- 8.4 Active Learning Methods -- 8.5 Combining Active Learning with Semi-supervised Learning -- 8.6 Applications -- 8.7 Evaluation of Active Learning Methods -- 8.8 Discussion and Conclusions -- References -- PART 2 SPOKEN LANGUAGE UNDERSTANDING FOR HUMAN/HUMAN CONVERSATIONS -- 9 Human/Human Conversation Understanding (Gokhan Tur and Dilek Hakkani-T�ur) -- 9.1 Background -- 9.2 Human/Human Conversation Understanding Tasks -- 9.3 Dialogue Act Segmentation and Tagging -- 9.4 Action Item and Decision Detection -- 9.5 Addressee Detection and Co-reference Resolution -- 9.6 Hot Spot Detection -- 9.7 Subjectivity, Sentiment, and Opinion Detection -- 9.8 Speaker Role Detection -- 9.9 Modeling Dominance -- 9.10 Argument Diagramming -- 9.11 Discussion and Conclusions -- References -- 10 Named Entity Recognition (Fr�d�ric B�chet) -- 10.1 Task Description -- 10.2 Challenges Using Speech Input -- 10.3 Benchmark Data Sets, Applications -- 10.4 Evaluation Metrics -- 10.5 Main Approaches for Extracting NEs from Text -- 10.6 Comparative Methods for NER from Speech -- 10.7 New Trends in NER from Speech -- 10.8 Conclusions -- References -- 11 Topic Segmentation (Matthew Purver) -- 11.1 Task Description -- 11.2 Basic Approaches, and the Challenge of Speech -- 11.3 Applications and Benchmark Datasets -- 11.4 Evaluation Metrics -- 11.5 Technical Approaches -- 11.6 New Trends and Future Directions -- References -- 12 Topic Identification (Timothy J. Hazen) -- 12.1 Task Description -- 12.2 Challenges Using Speech Input -- 12.3 Applications and Benchmark Tasks -- 12.4 Evaluation Metrics -- 12.5 Technical Approaches -- 12.6 New Trends and Future Directions -- References -- 13 Speech Summarization (Yang Liu and Dilek Hakkani-T�ur).
505 8 _a13.1 Task Description -- 13.2 Challenges when Using Speech Input -- 13.3 Data Sets -- 13.4 Evaluation Metrics -- 13.5 General Approaches -- 13.6 More Discussions on Speech versus Text Summarization -- 13.7 Conclusions -- References -- 14 Speech Analytics (I. Dan Melamed and Mazin Gilbert) -- 14.1 Introduction -- 14.2 System Architecture -- 14.3 Speech Transcription -- 14.4 Text Feature Extraction -- 14.5 Acoustic Feature Extraction -- 14.6 Relational Feature Extraction -- 14.7 DBMS -- 14.8 Media Server and Player -- 14.9 Trend Analysis -- 14.10 Alerting System -- 14.11 Conclusion -- References -- 15 Speech Retrieval (Ciprian Chelba, Timothy J. Hazen, Bhuvana Ramabhadran and Murat Saradclar) -- 15.1 Task Description -- 15.2 Applications -- 15.3 Challenges Using Speech Input -- 15.4 Evaluation Metrics -- 15.5 Benchmark Data Sets -- 15.6 Approaches -- 15.7 New Trends -- 15.8 Discussion and Conclusions -- References -- Index.
506 _aRestricted to subscribers or individual electronic text purchasers.
520 _a"This book is the first to focus exclusively on this growing topic. It begins with basic coverage of typical approaches used in SLU, such as favourite classification methods and modeling techniques, and discussion of the terminology used. It then provides state of the art approaches for the application of SLU in both human/human communication, and spoken dialog systems"--
_cProvided by publisher.
530 _aAlso available in print.
538 _aMode of access: World Wide Web
588 _aDescription based on PDF viewed 10/24/2017.
650 0 _aSpeech processing systems.
_93831
650 0 _aSemantics.
_925788
650 0 _aDiscourse analysis.
_922450
650 0 _aCorpora (Linguistics)
_931261
655 0 _aElectronic books.
_93294
700 1 _aTur, Gokhan.
_931262
700 1 _aDe Mori, Renato.
_931263
710 2 _aIEEE Xplore (Online Service),
_edistributor.
_931264
710 2 _aWiley,
_epublisher.
_931265
776 0 8 _iPrint version:
_z9780470688243
856 4 2 _3Abstract with links to resource
_uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=8042134
942 _cEBK
999 _c75020
_d75020