MALLET (MAchine Learning for LanguagE Toolkit) & Dialog Systems


Notes:

The MALLET Java machine learning for language toolkit was used by many universities and companies for various applications, such as dialogue systems, social computing, and recommendation systems; however, mention of MALLET in the academic literature has markedly declined over the past five years, between 2013 and 2018.

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Resources:

Wikipedia:

References:

See also:

Dynamic Topic ModelingEllogon | LingPipe & Dialog SystemsMachine Learning & Chatbots


Sequential labeling for tracking dynamic dialog states
S Kim, RE Banchs – 2014 – oar.a-star.edu.sg
… A dialog manager is one of the key components of a dialog system, which aims at determining the system actions to generate appropriate responses … both approaches were trained on the training set with the same feature functions de- fined in Section 3.3 using MALLET 1 toolkit …

Spoken language understanding for a nutrition dialogue system
M Korpusik, J Glass – IEEE/ACM Transactions on Audio …, 2017 – ieeexplore.ieee.org
… Nutrition Dialogue System … This paper presents ongoing language understanding experiments conducted as part of a larger effort to create a nutrition dialogue system that automatically extracts food concepts from a user’s spoken meal description …

Clarifying commands with information-theoretic human-robot dialog
R Deits, S Tellex, P Thaker… – Journal of Human …, 2013 – humanrobotinteraction.org
Page 1. Clarifying Commands with Information-Theoretic Human-Robot Dialog Robin Deits1 Battelle Memorial Institute, Columbus, OH Stefanie Tellex1, Pratiksha Thaker, Dimitar Simeonov MIT Computer Science and Artificial …

Using paraphrases and lexical semantics to improve the accuracy and the robustness of supervised models in situated dialogue systems
C Gardent, LMR Barahona – Conference on Empirical …, 2013 – hal.archives-ouvertes.fr
… 2004. Data-driven strategies for an automated dialogue system. In ACL, pages 71–78. Ian Richard Lane, Tatsuya Kawahara, and Shinichi Ueno. 2004 … Andrew Kachites McCallum. 2002. Mallet : A ma- chine learning for language toolkit. http ://mal- let.cs.umass.edu …

Toward incremental dialogue act segmentation in fast-paced interactive dialogue systems
R Manuvinakurike, M Paetzel, C Qu… – Proceedings of the 17th …, 2016 – aclweb.org
… It’s important to allow users to speak naturally to spoken dialogue systems … In our sequential pipeline, the first step is to use sequential tagging with a CRF (Conditional Ran- dom Field) (Lafferty et al., 2001) implemented in Mallet (McCallum, 2002) to perform the segmen- tation …

Multimodality and dialogue act classification in the RoboHelper project
L Chen, B Di Eugenio – Proceedings of the SIGDIAL 2013 Conference, 2013 – aclweb.org
… We used Mallet (McCallum, 2002) to build CRF mod- els … However, dif- ferent from other sequence labeling problems such as part-of-speech tagging, a dialogue system can- not wait until the whole dialogue ends to classify the current DA …

Conditional random fields for responsive surface realisation using global features
N Dethlefs, H Hastie, H Cuayáhuitl… – Proceedings of the 51st …, 2013 – aclweb.org
… In text generation, cohesion can span over the entire text. In interactive settings such as gen- eration within a spoken dialogue system (SDS), a … which is computed using the Viterbi algorithm. We use the Mallet package1 (McCallum, 2002) for parameter learning and inference …

Learning dialogue management models for task-oriented dialogue with parallel dialogue and task streams
E Ha, C Mitchell, K Boyer, J Lester – Proceedings of the SIGDIAL 2013 …, 2013 – aclweb.org
… To support a task-oriented dialogue system capa- ble of not only responding to users’ dialogue in- put but also providing spontaneous system inter- vention during users’ task activities, a dialogue manager should provide two functionalities … This work used MALLET …

A discriminative sequence model for dialog state tracking using user goal change detection
Y Ma, E Fosler-Lussier – Spoken Language Technology …, 2014 – ieeexplore.ieee.org
… Most state-of-the-art spoken dialog systems assume the user goal is fixed during a dialog such that they do not have to deal with detecting misunderstandings versus goal change … We train the CRF using the MALLET toolkit [12], using gradient ascent optimization …

A simultaneous recognition framework for the spoken language understanding module of intelligent personal assistant software on smart phones
C Lee, Y Ko, J Seo – Proceedings of the 53rd Annual Meeting of the …, 2015 – aclweb.org
… In addition, since the SLU module in the previous dialogue systems has a complicated architecture that is composes of many sub-modules, it is difficult for them to be directly applied into the SLU module of intelli- gent … The Mallet toolkit was chosen for our CRF model (McCallum …

Integrating sequence information in the audio-visual detection of word prominence in a human-machine interaction scenario
A Schnall, M Heckmann – Fifteenth Annual Conference of the …, 2014 – isca-speech.org
… 155–175, 2004. [6] I. Bulyko, K. Kirchhoff, M. Ostendorf, and J. Goldberg, “Error- correction detection and response generation in a spoken dialogue system,” Speech Communication, vol … [23] C. Sutton, “Grmm: Graphical models in mallet,” http://mallet.cs.umass.edu/grmm/, 2006 …

Constructing Language Models for Spoken Dialogue Systems from Keyword Set
K Komatani, S Mori, S Sato – … Challenges and Solutions in Applied Artificial …, 2013 – Springer
… EACL, pp. 157–165 (2009) 7. Hakkani-Tur, D., Rahim, M.: Bootstrapping language models for spoken dialog systems from the world wide web. In: Proc … 230–237 (2004) 11. McCallum, AK: Mallet: A machine learning for language toolkit (2002), http://mallet.cs.umass.edu/ 12 …

Learning for spoken dialog systems with discriminative graphical models
Y Ma – 2015 – search.proquest.com
… Unfortunately, this problem still remains challenging for many state-of-the-art probabilistic dialog systems and this issue is mostly ignored … We train the CRF based on the MALLET toolkit [33] using gradient ascent optimization method for maximum likelihood parameter estimation …

Semantic Features for Dialogue Act Recognition
P Král, L Lenc, C Cerisara – International Conference on Statistical …, 2015 – Springer
… Sapporo, Japan (2003)Google Scholar. 24. Liang, WB, Wu, CH, Chen, CP: Semantic information and derivation rules for robust dialogue act detection in a spoken dialogue system … McCallum, AK: Mallet: a machine learning for language toolkit (2002) …

Training an integrated sentence planner on user dialogue
B McMahan, M Stone – Proceedings of the SIGDIAL 2013 Conference, 2013 – aclweb.org
… 2002. MALLET: A MAchine learning for LanguagE toolkit. http://mallet.cs.umass.edu. Tim Paek and Roberto Pieraccini … 2011. Reinforce- ment Learning for Adaptive Dialogue Systems: A Data-driven Methodology for Dialogue Manage- ment and Natural Language Generation …

Dialogue act recognition in synchronous and asynchronous conversations
M Tavafi, Y Mehdad, S Joty, G Carenini… – Proceedings of the …, 2013 – aclweb.org
… the underlying conversational struc- ture in dialogues is important for detecting the human social intentions in spoken conversations and in many applications including summariza- tion (Murray, 2010), dialogue systems and di … We use the Mallet package3 for the CRF algorithm …

Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month
R Thackeray, SH Burton… – BMC …, 2013 – bmccancer.biomedcentral.com
… Statistical methods included ANOVA and chi square. For content analysis, we used computational linguistics techniques, specifically the MALLET implementation of the unsupervised topic modeling algorithm Latent Dirichlet Allocation. Results …

A Mixed-Initiative System for Human-Robot Interaction with Multiple UAVs in Search and Rescue Missions
G Bevacqua, J Cacace, A Finzi, V Lippiello – 2014 – aiia2014.di.unipi.it
… [7] L. Lucignano, F. Cutugno, S. Rossi, A. Finzi A dialogue system for multimodal human-robot interaction … 2 Page 3. [10] A. Ollero, S. Lacroix, L. Merino, J. Gancet, J. Wiklund, V. Remuss, IV Perez, LG Gutierrez, DX Viegas, MAG Benitez, A. Mallet, R. Alami, R. Chatila, G. Hommel …

Fudannlp: A toolkit for chinese natural language processing
X Qiu, Q Zhang, X Huang – Proceedings of the 51st Annual Meeting of …, 2013 – aclweb.org
… Currently, our toolkit has been used by many universities and companies for various applications, such as the dialogue system, so- cial computing, recommendation … Similar to Mallet (Mc- Callum, 2002), we use the pipeline structure for a flexible transformation of various data …

A noisy channel approach to error correction in spoken referring expressions
SN Kim, I Zukerman, T Kleinbauer… – Proceedings of the Sixth …, 2013 – aclweb.org
… Domingos and Pazzani, 1997) (cs. waikato.ac.nz/ml/weka/), and the Mallet im- plementation of the linear chain Conditional Ran- dom Fields (CRF) algorithm (Lafferty et al., 2001) (mallet.cs.umass.edu). The best performance was …

Multimodal Fusion as Communicative Acts during Human–Robot Interaction
F Alonso-Martín, JF Gorostiza, M Malfaz… – Cybernetics and …, 2013 – Taylor & Francis
… Research on dialog systems is a very active area in social robotics … The dialogue manager (IDiM) is one of the components of the robotic dialog system (RDS) and is in charge of managing the dialogue flow during the conversational turns …

A Comparison of Normalization Techniques Applied to Latent Space Representations for Speech Analytics
M Morchid, R Dufour, D Matrouf – Sixteenth Annual Conference of …, 2015 – isca-speech.org
… To find the best operating point (ie the best topic space configuration), 500 topic spaces are elaborated with a LDA by varying the number n of topics for each topic space from 5 to 505 and using the LDA Mallet Java implementation2 … This 2http://mallet.cs.umass.edu/ 147 Page 4 …

Real-time understanding of complex discriminative scene descriptions
R Manuvinakurike, C Kennington, D DeVault… – Proceedings of the 17th …, 2016 – aclweb.org
… The pipeline is designed how- ever for eventual real-time operation using incre- mental ASR results, so that in the future it can be incorporated into a real-time interactive dialogue system … plemented with Mallet (McCallum, 2002)) …

SpeakerLDA: Discovering Topics in Transcribed Multi-Speaker Audio Contents
D Spina, JR Trippas, L Cavedon… – Proceedings of the Third …, 2015 – dl.acm.org
… There- fore, the same sampling methods such as Gibbs sampling—and likewise, existent LDA implementations such as MALLET [18]— can be … according to topic similarity may im- prove the application of current strategies for information presen- tation in dialog systems [8]. In …

Context-Dependent Error Correction of Spoken Referring Expressions
I Zukerman, A Partovi, SN Kim – Sixteenth Annual Conference of …, 2015 – isca-speech.org
… the Mallet implementation of the linear chain Conditional Random Fields (CRF) algorithm [22] to learn se- quences of semantic labels (mallet.cs.umass.edu) … [12] R. López-Cózar and D. Griol, “New technique to enhance the per- formance of spoken dialogue systems based on …

Topic Stability over Noisy Sources
J Su, O Boydell, D Greene, G Lynch – arXiv preprint arXiv:1508.01067, 2015 – arxiv.org
… Similarly we perform 5 runs of each Mallet LDA (McCallum, 2002) topic model as the algorithm initial state is determined by a random seed … Marc Cavazza. 2001. An empirical study of speech recognition errors in a task-oriented dialogue system …

Query Refinement Using Conversational Context: A Method and an Evaluation Resource
M Habibi, A Popescu-Belis – … on Applications of Natural Language to …, 2015 – Springer
… The topic distributions are created using the LDA topic modeling technique [5], implemented in the Mallet toolkit [20] … 120–127 (2001)Google Scholar. 20. McCallum, AK: MALLET: A machine learning for language toolkit (2002). http://mallet.cs.umass.edu. 21 …

Assisting Composition of Email Responses: a Topic Prediction Approach
S Gella, M Dymetman, JM Renders… – arXiv preprint arXiv …, 2015 – arxiv.org
… For learning the LDA topic models (as described in section 4), we have used MALLET (McCallum, 2002) toolkit, with the standard (default) setting. We evaluate our methods using three metrics: 1. Bhattacharya coefficient (Bhattacharya, 1943) …

The coordinating role of language in real-time multimodal learning of cooperative tasks
M Petit, S Lallée, JD Boucher… – IEEE Transactions …, 2013 – ieeexplore.ieee.org
… 1) Interaction Management: Interaction management is provided by the CSLU Toolkit [42] rapid application devel- opment (RAD) state-based dialog system which combines state-of-the-art speech synthesis (Festival) and recognition (Sphinx-II recognizer) in a GUI programming …

Multi-Task CRF Model for Predicting Issue Resolution Status in Social Media based Customer Care
A Agarwal, S Kataria – 2014 – umiacs.umd.edu
Page 1. Multi-Task CRF Model for Predicting Issue Resolution Status in Social Media based Customer Care Arvind Agarwal Palo Alto Research Center Webster, New York, USA arvind.agarwal@xerox.com Saurabh Kataria Palo …

Computational discourse analysis
M Dascalu – Analyzing Discourse and Text Complexity for Learning …, 2014 – Springer
… 1. Cambridge University Press, Cambridge (2008)MATHGoogle Scholar. Manning, CD, Schütze, H.: Foundations of statistical Natural Language Processing. MIT Press, Cambridge (1999)MATHGoogle Scholar. McCallum, AK: MALLET: A Machine Learning for Language Toolkit …

Patients’ involvement in e-health services quality assessment: a system for the automatic interpretation of SMS-based patients’ feedback
S Rubrichi, A Battistotti, S Quaglini – Journal of biomedical informatics, 2014 – Elsevier
… This can be seen as a way to “capture” the hidden patterns of labels and features, and “learn” what the likely output might be, given these patterns. Our system uses the MALLET [39] implementation of CRFs. 4. Results. 4.1. Classification algorithm performance …

Natural language processing in serious games: a state of the art
D Picca, D Jaccard, G Eberlé – International Journal of …, 2015 – pdfs.semanticscholar.org
… next question. For further details on the Finite State Automaton, refer to Section 3.1. The learner’s answer is classified into a dialogue act using a trained Logistic-Regression classifier (taken from the Mallet toolkit). Then, the …

Mixed-Initiative Planning and Execution for Multiple Drones in Search and Rescue Missions.
G Bevacqua, J Cacace, A Finzi, V Lippiello – ICAPS, 2015 – aaai.org
Page 1. Mixed-Initiative Planning and Execution for Multiple Drones in Search and Rescue Missions Giuseppe Bevacqua, Jonathan Cacace, Alberto Finzi, Vincenzo Lippiello DIETI, Universit`a degli Studi di Napoli Federico …

No Evidence Left Behind: Understanding Semantics in Dialogs using Relational Evidence Based Learning
A Celikyilmaz, D Hakkani-Tur, M Jeong – microsoft.com
… the baselines. 1 Introduction A typical spoken language understanding (SLU) en- gine of a conversational dialog system represents utterances of different domains (eg, news, travel, etc.) with semantic components. These compo …

Identifying narrative clause types in personal stories
R Swanson, E Rahimtoroghi, T Corcoran… – Proceedings of the 15th …, 2014 – aclweb.org
… Reid Swanson, Elahe Rahimtoroghi, Thomas Corcoran and Marilyn A. Walker Natural Language and Dialog Systems Lab University of California … This feature encoding was used for machine learn- ing experiments with classification algorithms from Mallet (McCallum, 2002 …

Document-level school lesson quality classification based on German transcripts.
L Flekova, T Sousa, M Mieskes, I Gurevych – JLCL, 2015 – jlcl.org
… Additionally, we built topic models on the teacher’s and students’ speech in high and low rated lessons using Mallet topic modelling tools (McCallum, 2002) empirically set to 50 topics. See Table 6 for an example of topics used in this feature group. 5.2 …

Statistical Dialog Management for Health Interventions
U Yasavur – 2014 – digitalcommons.fiu.edu
… Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains … based on the brief intervention counseling style via spoken dialogue systems …

Big data driven natural language processing research and applications
VN Gudivada, D Rao, VV Raghavan – Handbook of Statistics, 2015 – Elsevier
… These results are used in other tasks such as co-reference resolution, word-sense disambiguation, semantic parsing, question answering, dialog systems, textual entailment, information extraction, information retrieval, and text summarization …

Dialogue act recognition in synchronous and asynchronous conversations
T Maryam – 2013 – open.library.ubc.ca
Learning, knowledge, research, insight: welcome to the world of UBC Library, the second-largest academic research library in Canada.

Overview of NTCIR-12.
K Kishida, MP Kato – NTCIR, 2016 – research.nii.ac.jp
… We considered the task as a slight variation of supervised machine learning classification problem. Our strategy involves building models on different standard classifiers based on probabilistic and entropy models from MALLET, a Natural Language Processing tool …

Scope of ontological annotation in e-commerce
S Asharaf, MS Abdulla – International Journal of Business …, 2013 – inderscienceonline.com
… automated ontology generation, an example being the conversion of classifications derived from MALLET, sometimes after mere parsing of a document repository, into OWL ontologies, as seen in Giunchiglia et al. (2008). A natural-language-based dialogue system for physical …

Question answering in conversations: Query refinement using contextual and semantic information
M Habibi, P Mahdabi, A Popescu-Belis – Data & Knowledge Engineering, 2016 – Elsevier
… the query Q made of query words q. The topic distributions are created using the LDA (Latent Dirichlet Analysis) topic modeling technique [30], implemented in the Mallet toolkit [31]. The topic models are learned over a large …

Extracting audio summaries to support effective spoken document search
D Spina, JR Trippas, L Cavedon… – Journal of the …, 2017 – Wiley Online Library
By continuing to browse this site you agree to us using cookies as described in About Cookies. Remove maintenance message …

A framework for meaning aware product discovery in e-commerce
S Asharaf, VS Anoop, AL Afzal – Encyclopedia of E-Commerce …, 2016 – igi-global.com
… automated ontology generation, an example being the conversion of classifications derived from MALLET, sometimes after mere parsing of a document repository, into OWL ontologies, as seen in (Giunchiglia et. al., 2008). A natural-language based dialogue system for physical …

The use of Natural Language Processing techniques to support Health Literacy: an evidence-based review
P Moreda, E Lloret – 2015 – rua.ua.es
Page 1. The use of Natural Language Processing techniques to support Health Literacy: an evidence-based review Paloma Moreda, Elena Lloret Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain Abstract …

SENSEI Coordinator
M Kabadjov, EA Stepanov, F Celli, SA Chowdhury… – sensei-conversation.eu
… Consequently, the range of applications of DA analysis is quite wide and includes conversa- tion summarization (both spoken and written), dialogue systems, etc.; and DAs have been extensively studied in both theoretical and computational linguistics …

Intelligence Virtual Analyst Capability: Governing Concepts and Science and Technology Roadmap
A Bergeron-Guyard, V Lavigne, D Poussart, D Gouin… – 2014 – dtic.mil
Page 1. Intelligence virtual analyst capability Governing concepts and science and technology roadmap Alexandre Bergeron-Guyard Valérie Lavigne Denis Poussart Denis Gouin Jean Roy DRDC – Valcartier Research Centre Defence Research and Development Canada …

Reasoning based on consolidated real world experience acquired by a humanoid robot
M Petit, G Pointeau, PF Dominey – Interaction Studies, 2016 – jbe-platform.com
… Spoken language has been used to “program” robots, by specifying procedures to achieve tasks, including navigation (Lauria, Bugmann, Kyriacou, & Klein, 2002), interaction (Dominey, Mallet, & Yoshida, 2007a, 2007b; Dominey & Mallet, 2009; Doshi & Roy, 2008; McGuire et al …

Development of an Autonomous Character in Karate Kumite
K Petri, K Witte, N Bandow, P Emmermacher… – … on Computer Science in …, 2017 – Springer
… de Kok, I., Hough, J., Hülsmann, F., Waltemate, T., Botsch, M., Schlangen, D., Kopp, S.: Demonstrating the dialogue system of the intelligent coaching space … Miles, HC, Pop, SR, Watt, SJ, Lawrence, GP, John, NW, Perrot, V., Mallet, P., Mestre, DR, Morgan, K.: Efficacy of a virtual …

Domain-and Language-adaptable Natural Language Controlling Framework
P Barabás, I Juhász – 2013 – hjphd.iit.uni-miskolc.hu
… vi QLF Quasi-Logical Form RDF Resource Description Framework SDK Software Development Kit SDS Speech Dialog System SNLP Stanford NLP SNLPG Stanford Natutal Language Processing Group SPO Subject-Predicate-Object SRM Semantic Representation Model TAG …

DCG-UPUP-Away: automatic symbol acquisition through grounding to unknowns
M Tucker – 2016 – dspace.mit.edu
Page 1. Automatic Symbol Acquisition through Grounding to Unknowns by Mycal Tucker SB Massachusetts Institute of Technology (2015) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of …

Towards Modeling Collaborative Task Oriented Multimodal Human-human Dialogues
L Chen – 2014 – search.proquest.com
… INTRODUCTION. A dialogue system is a computer system intended to converse with a human … The most widely researched and developed dialogue systems are spoken dialogue systems, which are also known as spoken language systems (Jurafsky and Martin, 2009) …

DOMAIN-AND LANGUAGE-ADAPTIVE NATURAL LANGUAGE CONTROLLING FRAMEWORK
P Barabás – 2013 – 193.6.1.94
… vi OWL Web Ontology Langauge POI Point Of Interests POS Part-Of-Speech QLF Quasi-Logical Form RDF Resource Description Framework SDK Software Development Kit SDS Speech Dialog System SNLP Stanford NLP SNLPG Stanford Natutal Language Processing Group …

Natural language processing with Java and LingPipe Cookbook
B Baldwin, K Dayanidhi – 2014 – books.google.com
… Since first being introducedto the fieldin 2006,hehas worked ondiverse problems suchas spoken dialog systems, machine translation, text normalization, coreference resolution, and speechbased information retrieval, leadingto publications in esteemed conferences suchas …

A statistical, grammar-based approach to microplanning
C Gardent, L Perez-Beltrachini – Computational Linguistics, 2017 – MIT Press
… content ordering, lexicalization, and aggregation. SPoT is part of a dialog system in the travel domain, which was later on extended to provide restaurant information (SPaRKy; Walker et al. 2007). In this approach, each input …

Effective use of cross-domain parsing in automatic speech recognition and error detection
M Marin – 2015 – digital.lib.washington.edu
… information, we attempt to detect their location and extent (within the ASR hypothesis), as well as the type, in order to handle them effectively during the subsequent clarification request made by the dialog system component. In particular we are interested in two types …

NLTK essentials
N Hardeniya – 2015 – books.google.com
… probabilistic model 67 Speech recognition 68 Text classification 68 Information extraction 70 Question answering systems 70 Dialog systems 71 Word … Here is a small list of available NLP tools: • GATE • Mallet • Open NLP • UIMA • Stanford toolkit • Genism • Natural Language …

Methodologies for realizing natural-language-facilitated human-robot cooperation: A review
R Liu, X Zhang – arXiv preprint arXiv:1701.08756, 2017 – arxiv.org
Page 1. submitted to Knowledge-based Systems, January 2017 Methodologies realizing natural-language-facilitated human-robot cooperation: A review Rui Liu, Xiaoli Zhang* Department of Mechanical Engineering, Colorado …

Leveraging Pragmatic Features for Microblogged Information Extraction During Crises
W Corvey – 2013 – scholar.colorado.edu
… 55 4.4 Territory of Information . . . . . 55 4.4.1 Territory and Dialogue Systems . . . . . 56 4.4.2 Territory of Information Annotation . . . . . 56 4.4.3 Summary …

Fuzzy topic modeling for medical corpora
A Karami – 2015 – search.proquest.com
… This technique was used to extract clinical concepts from psychiatric narratives [47]. According to [48] LSA was used to extract semantic words and semantic concepts for developing an ontology-based speech act identication in a bilingual dialogue system …

A Corpus Driven Computational Intelligence Framework for Deception Detection in Financial Text
SZ Minhas – 2016 – dspace.stir.ac.uk
… 4.9.1 Gibbs Sampling Based Latent Dirichlet Allocation (LDA) Algorithm ….. 132 4.9.2 Mallet and Results ….. 135 4.10 Concept Mining …

Personalizing recurrent-neural-network-based language model by social network
HY Lee, BH Tseng, TH Wen, Y Tsao, HY Lee… – IEEE/ACM Transactions …, 2017 – dl.acm.org
… extracting user character- istic features. Here we used the MALLET toolkit [58] to train a Latent Dirichlet Allocation (LDA) [59] topic model. The testing experiments were conducted on a crawled Facebook corpus. A total of 42 …

Evaluating the Effectiveness of Immersive Interfaces for Combat Training
A Butler, R Fowler, M Winkel – 2015 – dtic.mil
Page 1. Standard Form 298 (Rev 8/98) Prescribed by ANSI Std. Z39.18 956-665-2534 W911NF-11-1-0126 59095-CS-REP.2 Final Report a. REPORT 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: This project focuses directly on immersive science …

An Interactive Visualisation for Definite Clause Grammars
J Kalkus – pub.informatik.uni-wuerzburg.de
… With the help of a dialogue system, it offers children the opportu- nity to experiment with grammars in Prolog. Queries can be made to a previously specified grammar … S. Mallet and M. Ducassé created MYRTLE in 1999 [MD99] for deductive databases debugging …

Spoken Term Detection and Spoken Word Sense Induction on Noisy Data
J Chiu – 2015 – cs.cmu.edu
… 11 2.1.1 Word Recurrence in Dialogue Systems … 2.1.1 Word Recurrence in Dialogue Systems (Barnett, 1973) propose the “Thematic Memory” as the content-word equivalent of the user-state syntax model …

Developmental reasoning and planning with robot through enactive interaction with human
M Petit – 2014 – hal.archives-ouvertes.fr
Page 1. Developmental reasoning and planning with robot through enactive interaction with human Maxime Petit To cite this version: Maxime Petit. Developmental reasoning and planning with robot through enactive interaction with human. Automatic …

EMNLP versus ACL: Analyzing NLP research over time
SD Gollapalli, X Li – Proceedings of the 2015 Conference on Empirical …, 2015 – aclweb.org
… Page 3. Topic ID Top Words 0 System, Dialogue, Dialogue System, Information, Speech Recognition, Speech, Dialogue Manager, Data Collection, User Utterances 1 Model … The LDA implemen- tation provided in Mallet (McCallum, 2002) was used to extract topics from this matrix …

Medical event timeline generation from clinical narratives
P Raghavan – 2014 – search.proquest.com
… Moreover, the proposed WFST-based framework may be useful in modeling multi-alignments across a variety of domains such as spoken dialog systems and speech. Information Fusion (Chapter 8). Information is captured in both structured and. unstructured formats in the EHR …

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