Latent Semantic & Dialog Systems 2014


Notes:

  • Conversational Informatics

See also:

Latent Semantic & Dialog Systems 2011 | Latent Semantic & Dialog Systems 2012 | Latent Semantic & Dialog Systems 2013


Biomedical text mining: State-of-the-art, open problems and future challenges A Holzinger, J Schantl, M Schroettner, C Seifert… – … Discovery and Data …, 2014 – Springer … adapting latent semantic analysis to accurately extract clinical concepts from psychiatric narrative. Journal of Biomedical Informatics 41(6), 1070–1087 (2008) CrossRef; Yeh, JF, Wu, CH, Chen, MJ: Ontology-based speech act identification in a bilingual dialog system using … Cited by 4

Spoken Language Understanding for Natural Interaction: The Siri Experience JR Bellegarda – Natural Interaction with Robots, Knowbots and …, 2014 – Springer … Accessed Oct 2011 2. Bellegarda, JR: Latent semantic mapping. … J. Exp. Psychol. Gen. 135(2), 184–206 (2006) 7. Gasic, M., Keizer, S., Mairesse, F., Schatzmann, J., Thomson, B., Young, S.: Training and evaluation of the HIS POMDP dialogue system in noise. … Cited by 5 Related articles All 3 versions

Learning Situated Knowledge Bases through Dialog A Pappu, AI Rudnicky – Fifteenth Annual Conference of …, 2014 – mazsola.iit.uni-miskolc.hu … The study took place in the context of EventSpeak Dialog System that informs people about upcoming talks/events of their interest and ongo- ing work of other researchers on … For this purpose, we use Latent Semantic Indexing method as implemented in the GEN- SIM toolkit [29 … Cited by 1

Probabilistic enrichment of knowledge graph entities for relation detection in conversational understanding D Hakkani-Tür, A Celikyilmaz… – Proceedings of …, 2014 – mazsola.iit.uni-miskolc.hu … from web documents [6] and discovering new relation types from large text corpora [7]. Se- mantic knowledge graphs have also been used for SLU seman- tic parsing tasks in dialog systems [8, 9, 10 … [33] G. Tur, A. Celikyilmaz, and D. Hakkani-Tür, “Latent semantic modeling for … Cited by 1

Training a statistical surface realiser from automatic slot labelling H Cuayáhuitl, N Dethlefs, H Hastie, X Liu – 2014 – macs.hw.ac.uk … Our scenario is surface realisation of known and unknown dialogue acts within a spoken dialogue system in the restau- rant domain. … where simLSA(xi,xj) is the Latent Semantic Analysis (LSA) between clauses, D(xi,xj) is the minimal path dis- tance between terms within clauses … Cited by 1

A Semi-Supervised Clustering Approach for Semantic Slot Labelling H Cuayáhuitl, N Dethlefs, H Hastie – 2014 – macs.hw.ac.uk … [31] Y.-N. Chen, WY Wang, and AI Rudnicky, “Unsupervised induction and filling of semantic slots for spoken dialogue systems using frame- semantic parsing,” in ASRU, 2013. [32] G. Tür, A. Ç elikyilmaz, and D. Hakkani-Tür, “Latent semantic modeling for slot filling in … Cited by 1

Toward A Polish Intelligent Virtual Tutor: An Overview Of Existing Work I TRUCK, M DURAND, M WATOREK – World Scientific … It consists of a dialogue system planning implemented in Prolog for the tutor’s movements, a rule- based tagging, an expert model to compare given and expected answers Page 5. 476 by latent semantic analysis, and an interface with a talking head (speech synthesis) with …

Dialogue Strategies for Dialogue System: A Review S Arora – davasrijircs.in … 4.5 Tutorial dialogue system The … head. AutoTutor has seven modules: a curriculum script, language extraction, speech act classification, latent semantic analysis, topic selection, dialog move generation, and a talking head. … Related articles

Task Estimation Using Latent Semantic Analysis of Visual Scenes and Spoken Words M Kimura, S Sawada, Y Iribe… – Electronics and …, 2014 – Wiley Online Library … Research Article. Task Estimation Using Latent Semantic Analysis of Visual Scenes and Spoken Words. … The objects recognized in every frame are saved as text data. These words and objects are used as elements of the task vectors. 2.2 Latent semantic analysis. … Related articles All 2 versions

TSVD as a Statistical Estimator in the Latent Semantic Analysis Paradigm G Pilato, G Vassallo – ieeexplore.ieee.org … LATENT Semantic Analysis (LSA) is a technique based on linear algebra that tries to roughly capture and code the semantics of … such as natural language understanding, cognitive modeling, speech recog- nition, smart indexing, anti-spam filters, dialogue systems and other …

Conversation Architecture C Engine – ceur-ws.org … encountered. * The Topic Detector determines using Latent Semantic analysis that the topic is ”new account” using bag of words ”new”, ”account”, and ”open”. … 2000. The att-darpa communicator mixed-initiative spoken dialog system. In ICSLP. … Related articles

SAIL-GRS: Grammar Induction for Spoken Dialogue Systems using CF-IRF Rule Similarity K Zervanou, N Malandrakis, S Narayanan – SemEval 2014, 2014 – aclweb.org … In Proceedings of the Fifth IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems, pages 22–27. Yihong Gong and Xin Liu. 2001. Generic text summa- rization using relevance measure and latent semantic analysis. …

A Survey of Intelligent Language Tutoring Systems MA Emran, K Shaalan – Advances in Computing, …, 2014 – ieeexplore.ieee.org … 1. Latent Sematic Analysis Latent Semantic Analysis (LSA) is an NLP technique that measures the similarity between any two fragments of text (a … 6. Beetle II System Beetle II system is a tutorial dialogue system that has been implemented to accept input from the learner without …

Latent Semantic Rational Kernels for Topic Spotting on Conversational Speech C Weng, D Thomson, P Haffner, B Juang – 2014 – ieeexplore.ieee.org … NO., 1 Latent Semantic Rational Kernels for Topic Spotting on Conversational Speech Chao … Abstract—In this work, we propose latent semantic rational kernels (LSRK) for topic spotting on conversational speech. Rather than …

Issues Regarding the Use of Natural Language Discourse In Intelligent Tutoring Systems PI Pavlik Jr, X Hu, DM Morrison – Design Recommendations for Intelligent … – gifttutoring.org … continues with work by Morrison, Nye, and Hu (chapter 19) that introduces some tech- nical concerns in dialogue systems centered on the … of responses (eg, true attempts by the student to provide an expected explanation) are further graded by using Latent Semantic Analysis or … Related articles All 2 versions

Efficient Language Model Construction for Spoken Dialog Systems by Inducting Language Resources of Different Languages T Misu, S Matsuda, E Mizukami, H Kashioka… – Natural Interaction with …, 2014 – Springer … machine translation systems for language portability of dialogue systems. In: Proceedings of Inter- national Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5612–5615 (2011) 10. Kim, W., Khudanpur, S.: Lexical triggers and latent semantic analysis for … Related articles All 3 versions

AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring BD Nye, AC Graesser, X Hu – … Journal of Artificial Intelligence in Education, 2014 – Springer … Cognition and Instruction, 24(4), 565–591. CrossRef; Deerwester, S., Dumais, ST, Furnas, GW, Landauer, TK, & Harshman, R. (1990). Indexing by latent semantic analysis. … Using a domain-independent reactive planner to implement a medical dialogue system. …

SAWDUST: a Semi-Automated Wizard Dialogue Utterance Selection Tool for domain-independent large-domain dialogue S Gandhe, D Traum – 15th Annual Meeting of the Special …, 2014 – anthology.aclweb.org … First is the traditional Wizard- of-Oz dialogue collection, where a wizard inter- acts with a user of the dialogue system. … 2008. Using random in- dexing to improve singular value decomposition for latent semantic analysis. In Proceedings of LREC’08, Morocco. …

Computational Discourse Analysis M Dascalu – Analyzing Discourse and Text Complexity for Learning …, 2014 – Springer … 2010); 3/ lexically or semantically related words obtained from semantic distances in ontologies (Budanitsky and Hirst 2006) (see 4.3.1 Semantic Distances and Lexical Chains), cosine similarity in vector spaces from Latent Semantic Analysis (Landauer et al. … Related articles

Bielefeld SC: Orthonormal Topic Modelling for Grammar Induction JP McCrae, P Cimiano – SemEval 2014, 2014 – anthology.aclweb.org … 1 Introduction Grammar induction is the task of inducing high- level rules for application of grammars in spoken dialogue systems. … 1990. Indexing by latent semantic analysis. JASIS, 41 (6): 391–407. Evgeniy Gabrilovich and Shaul Markovitch. 2007. …

Automatic dialogue act recognition with syntactic features P Král, C Cerisara – Language Resources and Evaluation, 2014 – Springer … 2006 ) and C-STAR (Blanchon and Boitet 2000 ) machine translation and dialogue systems that rely on dialogue act classification. … 2006 ), latent semantic analysis (Serafin and Di Eugenio 2004 ), hidden backoff models (Bilmes 2005 ), maximum entropy models (Ang et al. … Related articles All 4 versions

A Hybrid Language Understanding Approach for Robust Selection of Tutoring Goals R Srivastava, K VanLehn – cs.cmu.edu … 2001. Initiative management for tutorial dialogue. In Proceedings of the NAACL Workshop Adaption in Dialogue Systems. 5] MS Glass. 1999. … 8] TK Landauer, PW Foltz, and D. Laham. 1998. Introduction to latent semantic analysis. To Appear in Discourse Processes. … Related articles All 2 versions

Chatbots as Interface to Ontologies A Augello, G Pilato, G Vassallo, S Gaglio – Advances onto the Internet of …, 2014 – Springer … Even if the simple technology allows to easily implement a dialogue system, the obtained conversation is limited by pattern matching rules on which … We believe that this intuitive-associative capability can be obtained using the LSA (Latent Semantic Analysis) methodology [20]. … Related articles All 2 versions

Performance of a trialogue-based prototype system for English language assessment for young learners K Evanini, Y So, J Tao, D Zapata-Rivera, C Luce… – wocci.org … 2See [12] for a description of a system that used different spoken dialogue system components to implement the same tasks. 4.2. … in each dialog state was conducted using a hybrid approach consisting of both hand-crafted regular expressions and Latent Semantic Analysis (LSA …

Combining Task and Dialogue Streams in Unsupervised Dialogue Act Models A Ezen-Can, KE Boyer – 15th Annual Meeting of the Special Interest …, 2014 – aclweb.org … This work constitutes a step toward building high-performing unsupervised dialogue act models that will be used in the next generation of task-oriented dialogue systems. 1 Introduction Dialogue acts represent the underlying …

Cluster based Chinese Abbreviation Modeling Y Shi, YC Pan, MY Hwang – Fifteenth Annual Conference …, 2014 – mazsola.iit.uni-miskolc.hu … In some practical applications (eg dialogue systems and voice search systems), document level context information is not available. … 47–58, 2006. [22] Y. cheung Tam and T. Schultz, “Unsupervised language model adaptation using latent semantic marginals,” in In Proc. …

Automatic Dialogue Act Recognition with Syntactic P Král, C Cerisara – textmining.zcu.cz … large applicative systems, such as the VERBMOBIL [14], NE- SPOLE [15] and C-STAR [16] machine translation and dialogue systems that rely … 35], Decision Trees [36], Neural Networks [37], but also more advanced approaches such as Boosting [38], Latent Semantic Anal- ysis … Related articles All 2 versions

Towards Assessing Students’ Prior Knowledge From Tutorial Dialogues D Stefanescu, V Rus, AC Graesser – educationaldatamining.org … Also, their work was in the context of a spoken dialogue system, while ours focuses on a text/chat-based conversational ITS. … Latent Semantic Analysis Models on Wikipedia and TASA, LREC [20] Taraban, R., and Rynearson, K. (1998). …

Question Classification in an Epistemic Game H Li, B Samei, AM Olney, AC Graesser, DW Shaffer – 2014 – edgaps.org … The prior research on automated question classification focused on ei- ther the feature selections in dialog systems [10,11] or question taxonomy in … The answer could be triggered by a series of attributes, such as latent semantic space analysis, speech act categories, five SKIVE … Related articles

Natural Language, Discourse, and Conversational Dialogues within Intelligent Tutoring Systems: A Review K Brawner, A Graesser – Design Recommendations for Intelligent Tutoring … – gifttutoring.org … Using latent semantic analysis to evaluate the contributions of students in AutoTutor. Interactive Learning Environments, 8 (2), 129-147. Haddad, WD (1978). … Paper presented at the Building Dialogue Systems for Tutorial Applications, Papers of the 2000 AAAI Fall Symposium. … Related articles All 2 versions

Toward Adaptive Unsupervised Dialogue Act Classification in Tutoring by Gender and Self-Efficacy A Ezen-Can, KE Boyer – strategies – research.csc.ncsu.edu … Unsupervised Spoken Language Understanding for a Multi- Domain Dialog System. IEEE Transactions On Audio, Speech, and Language Processing. 21, 11, 2451–2464. … FLSA: Extending Latent Semantic Analysis With Features For Dialogue Act Classification. …

Questions, pictures, answers M Theune, B van Schooten, R Op den Akker, W Bosma… – pure.uvt.nl … Enabling the user to give feedback on her information need is one of the purposes of our dialogue system. … in the figure indicate the similarity between the query (on the left) and the scopes of the images in the corpus (on the right), computed using Latent Semantic Analysis (see … Related articles

Domain Cartridge: Unsupervised Framework for Shallow Domain Ontology Construction from Corpus S Mukherjee, J Ajmera, S Joshi – Proceedings of the 23rd ACM …, 2014 – dl.acm.org … relations can be used for query expan- sion (eg by considering Synonyms along with the original query), interactive dialogue systems (eg for … Random Indexing can also be seen as an alternative to Latent Semantic Analysis [9]. Random Indexing is more scalable and al- lows for …

Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework I Titov, E Khoddam – arXiv preprint arXiv:1412.2812, 2014 – arxiv.org … benefit question answering [47, 29], textual entailment [46], machine translation [57, 36, 56, 21], and dialogue systems [5, 53 … roles) are jointly estimated by optimizing an objective which favours accurate reconstruction of arguments given the latent semantic representation (and …

Semantic Language Models For Automatic Speech Recognition AO Bayer, G Riccardi – sisl.disi.unitn.it … [2] JR Bellegarda, “Exploiting latent semantic information in statistical … [9] F. Zamora-Martinez, S. Espana-Boquera, J. Castro- Bleda, M., and R. De-Mori, “Cache neural network language models based on long-distance dependencies for a spoken dialog system,” in Proceedings …

Mining Gap-fill Questions from Tutorial Dialogues NB Niraula, V Rus, D Stefanescu, AC Graesser – educationaldatamining.org … Keywords Question Generation, Tutoring System, Dialogue Systems 1. INTRODUCTION Test construction is an expensive and time-consuming pro- cess for instructors and educational researchers. … We used a Latent Semantic …

Exploiting Psychological Factors for Interaction Style Recognition in Spoken Conversation WL Wei, CH Wu, JC Lin, H Li – IEEE/ACM Transactions on Audio, Speech …, 2014 – dl.acm.org … WORK Automatically extracting social meaning and intention from spoken dialogue is a crucial task for dialogue systems and so- cial … Knowledge Information Processing (CKIP) word segmentation system [29] was used to segment words, after which Latent Semantic Anal- ysis … Cited by 2 Related articles All 2 versions

Towards Identifying the Resolvability of Threads in MOOCs D Yang, M Wen, C Rose – EMNLP 2014, 2014 – aclweb.org … Thus, in addition to building on existing QA work in our feature engineering, we also introduce new directions, such as the linguistic modeling of speaker politeness, and conduct forms of latent semantic matching that have proven effective in dialogue systems. …

Unsegmented Dialogue Act Annotation and Decoding with N-Gram Transducers C Martinez-Hinarejos, J Benedi, V Tamarit – ieeexplore.ieee.org … 41], Bayesian Networks [42], regression trees [43], SVM and Latent Semantic Analysis [44]. The assumption of the segmentation (ie, knowing when the dialogue segments start and end inside a turn) is not realistic in some cases, such as for spoken dialogue systems and when …

Core technologies for the internet of services T Becker, C Burghart, K Nazemi, P Ndjiki-Nya… – Towards the Internet of …, 2014 – Springer … A platform for multimodal and situation aware dialog systems has been created, whose architecture and some applications are described. … This eliminates the frequent transformation steps between modules that are typical for earlier dialog systems. … Cited by 3

An Efficient Gradient-based Approach to Optimizing Average Precision Through Maximal Figure-of-Merit Learning I Kim, CH Lee – Journal of Signal Processing Systems, 2014 – Springer Page 1. J Sign Process Syst (2014) 74:285–295 DOI 10.1007/s11265-013-0748-0 An Efficient Gradient-based Approach to Optimizing Average Precision Through Maximal Figure-of-Merit Learning Ilseo Kim · Chin-Hui Lee Received … Cited by 1 Related articles All 4 versions

Metaphor Detection with Cross-Lingual Model Transfer YTLBA Gershman, ENC Dyer – demo.clab.cs.cmu.edu … tion, machine translation, dialog systems, senti- ment analysis, and text analytics, etc.) would have access to a potentially useful high-level bit of … Thus, vector space models can also be seen as vectors of (latent) semantic concepts, that preserve their “meaning” across languages … Cited by 1 Related articles All 2 versions

An attribute detection based approach to automatic speech processing SM Siniscalchi, CH Lee – Loquens, 2014 – loquens.revistas.csic.es … This number, often referred to as a CM, serves as a reference guide for the dialogue system to provide an appropriate response to its users, just as an … First, a vector representation of the spoken document is obtained using latent semantic analysis (LSA) (Bellegarda, 2000). …

Large vocabulary Russian speech recognition using syntactico-statistical language modeling A Karpov, K Markov, I Kipyatkova, D Vazhenina… – Speech …, 2014 – Elsevier … Syntactically enhanced latent semantic analysis (SELSA) has been investigated in Kanejiya et al. … and Nasr, 2009), a syntactic parser for spontaneous speech recognition outputs is used for identification of verbal sub-categorization frames for dialogue systems and spoken … Cited by 13 Related articles All 3 versions

Summer Internship Report O Kilic – cis.temple.edu … conversation logs via dialog systems (Artz and Zettlemoyer, 2011), and visual sensors (Matuszek et al., 2012) to approximate the best parsing. … in the summary. • Similarity: Employ a semantic similarity method (Latent semantic analysis or a knowledge base) …

Bringing machine learning and compositional semantics together P Liang, C Potts – stanford.edu … The pure semantic parsing task (section 4.1) is to learn an accurate mapping from utterances u to logical forms s. The interpretation task (sec- tion 4.2) is to learn an accurate mapping from utterances u to denotations d via latent semantic representations, in effect combining … Cited by 4 Related articles

Interpreting Natural Language Instructions Using Language, Vision, and Behavior L Benotti, T Lau, M Villalba – ACM Transactions on Interactive Intelligent …, 2014 – dl.acm.org … interaction. Moreover, the utterances in the corpora are quite short, with only five words on average; therefore, we believe that methods such as latent semantic analysis would not have an impact on overall performance. When … Cited by 1

A comparative study of evolving fuzzy grammar and machine learning techniques for text categorization NM Sharef, T Martin, KA Kasmiran, A Mustapha… – Soft Computing, 2014 – Springer … It has been utilized in many applications, such as dialogue systems, named entity recognition, information retrieval, and text categorization … A shallow semantic understanding was provided by the latent semantic analysis method (Salton and Buckley 1988), automated sentence …

Psychomime Classification Using Similarity Measures and Fuzzy c-Means Y Kurosawa, T Takezawa, TD Pham – Biomedical Informatics and …, 2014 – Springer Page 1. TD Pham et al. (Eds.): ACBIT 2013, CCIS 404, pp. 194–206, 2014. © Springer-Verlag Berlin Heidelberg 2014 Psychomime Classification Using Similarity Measures and Fuzzy c-Means Yoshiaki Kurosawa1,*, Toshiyuki Takezawa1, and Tuan D. Pham2 … Related articles All 2 versions

Robust and Fast Phonetic String Matching Method for Lyric Searching Based on Acoustic Distance XU Xin, K Tsuneo – IEICE TRANSACTIONS on Information and …, 2014 – search.ieice.org … In the text retrieval field, some fuzzy matching algorithms, such as Latent Semantic Index- ing (LSI) and partial matching, were used by major com- mercial Web search engines [14] to improve the robustness against incorrect queries. …

BEETLE II: Deep Natural Language Understanding and Automatic Feedback Generation for Intelligent Tutoring in Basic Electricity and Electronics M Dzikovska, N Steinhauser, E Farrow, J Moore… – International Journal of …, 2014 – Springer … Student input is matched against those expectations using latent semantic analysis. … aims was to investigate whether we can effectively handle more complex language by using a domain adaptation technique originally devel- oped for task-oriented spoken dialogue systems. …

Automatic scoring for answers to Arabic test questions WH Gomaa, AA Fahmy – Computer Speech & Language, 2014 – Elsevier … It has been used in the tutorial dialog system Why2-Atlas (VanLehn et al., 2002). … There are many corpus-based similarity techniques, such as Latent Semantic Analysis (LSA) (Landauer and Dumais, 1997), Explicit Semantic Analysis (ESA) (Gabrilovich and Markovitch, 2007 … Cited by 1 Related articles

Agile Facilitation for Collaborative Learning D Adamson – 2014 – cs.cmu.edu … In the context of a single-user conversational tutor, a set of conversational features, including measures of the quality and content of student answers as derived from Latent Semantic Analysis [48], have been successfully applied to predict the moment-to-moment affect of the … Related articles All 2 versions

An artificial neural network approach to automatic speech processing SM Siniscalchi, T Svendsen, CH Lee – Neurocomputing, 2014 – Elsevier An artificial neural network (ANN) is a powerful mathematical framework used to either model complex relationships between inputs and outputs or find patterns i. Cited by 2 Related articles

KIT-Conferences PI Lichtblau – 2014 – isl.anthropomatik.kit.edu … August 2009. Reliable evaluation of multimodal dialog systems, Florian Metze, Ina Wechsung, Stefan Schaffer, Julia Seebode, Sebastian Möller. Human Computer Interaction International, HCII 2009, San Diego, USA, 19. July 2009. …

Artificial Conversations for Chatter Bots Using Knowledge Representation, Learning, and Pragmatics C Chakrabarti – 2014 – repository.unm.edu … 22 2.2 The Syntactic Approach . . . . . 26 2.3 The Semantic Approach . . . . . 27 2.4 Dialogue systems . . . . . 27 viii Page 9. Contents 2.5 Limitations of existing approaches . . . . . 29 …

[BOOK] Conversational Informatics: A Data-Intensive Approach with Emphasis on Nonverbal Communication T Nishida, A Nakazawa, Y Ohmoto, Y Mohammad – 2014 – books.google.com … For sure, this text book will become an inspiring resource for students, teachers, and researchers that wish to go beyond traditional dialog systems and investigate the power and potential of social signals in human–computer interaction. Prof. … Cited by 1

The Eras and Trends of Automatic Short Answer Grading S Burrows, I Gurevych, B Stein – International Journal of Artificial …, 2014 – Springer Page 1. Int J Artif Intell Educ DOI 10.1007/s40593-014-0026-8 RESEARCH ARTICLE The Eras and Trends of Automatic Short Answer Grading Steven Burrows ·Iryna Gurevych ·Benno Stein © International Artificial Intelligence in Education Society 2014 …

Domain-sensitive topic management in a modular conversational agent framework D Macias Galindo – 2014 – researchbank.rmit.edu.au … Building Modular Knowledge Bases for Conversational Agents. In IJCAI Workshop on Knowledge Representation and Reasoning for Practical Dialogue Systems (KRPDS), pages 16–23, Barcelona, Spain, 2011a (ERA Rank: Unranked) …

Conversational Informatics T Nishida, A Nakazawa, Y Ohmoto, Y Mohammad – Springer … For sure, this text book will become an inspiring resource for students, teachers, and researchers that wish to go beyond traditional dialog systems and investigate the power and potential of social signals in human–computer interaction. Prof. …

Foundations and Trends® in Signal Processing L Deng, Y Dong – Signal Processing, 2014 – research.microsoft.com Page 1. the essence of knowledge FnT SIG 7:3-4 Deep Learning; Methods and Applications Li Deng and Dong Y u Foundations and Trends® in Signal Processing 7:3-4 Deep Learning Methods and Applications Li Deng and Dong Yu now now Page 2. 7.1. …

Automatically generating reading lists JG Jardine – … of Cambridge, Computer Laboratory, Technical Report, 2014 – cl.cam.ac.uk Page 1. Technical Report Number 848 Computer Laboratory UCAM-CL-TR-848 ISSN 1476-2986 Automatically generating reading lists James G. Jardine February 2014 15 JJ Thomson Avenue Cambridge CB3 0FD United Kingdom phone +44 1223 763500 … Related articles All 3 versions

Towards Modeling Collaborative Task Oriented Multimodal Human-human Dialogues L Chen – 2014 – indigo.uic.edu … tial multimodal dialogue systems. SmartKom was a mixed-initiative dialogue system with … tures from acoustics, and showed that prosodic cues can improve dialogue classification. (Di Eugenio et al., 2010) extended Latent Semantic Analysis (LSA) to Feature Latent Se- …

Modeling language with structured penalties AK Nelakanti – 2014 – tel.archives-ouvertes.fr … interactive machines. It has applications spanning across various domains, such as dialogue systems, text generation and machine translation among others and has been studied extensively in the past decades. Among problems …