NLTK & Dialog Systems 2015


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100 Best NLTK Videos | NLTK & Chatbots | NLTK & Natural Language Generation


The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems R Lowe, N Pow, I Serban, J Pineau – arXiv preprint arXiv:1506.08909, 2015 – arxiv.org … We seek a large dataset for research in dialogue systems with the following properties: • Two-way conversation, as opposed to multi- participant chat … Prior to applying each method, we perform stan- dard pre-processing of the data using the NLTK6 library and Twitter tokenizer7 … Cited by 25 Related articles All 12 versions

Understanding user’s cross-domain intentions in spoken dialog systems M Sun, YN Chen, AI Rudnicky – … on Machine Learning for SLU and …, 2015 – researchgate.net … 2.2 Interactive Dialog Task We also let users talk to a Wizard-of-Oz dialog system to reproduce (“reenact”) the multi-domain tasks in speech, instead of using the touch screen, in a controlled laboratory environment. … 2http://www.nltk.org/api/nltk.stem.html 3 Page 4. … Cited by 5 Related articles All 3 versions

Survey on chatbot design techniques in speech conversation systems SA Abdul-Kader, J Woods – Int. J. Adv. Comput. Sci. Appl.(IJACSA), 2015 – Citeseer … Because they are more natural than graphic-based interfaces, spoken dialogue systems are beginning to form the primary interaction method … B. Natural Language Toolkit (NLTK) In order to deal with and manipulate the text resulting from speech recognition and speech to text … Cited by 2 Related articles All 2 versions

A Study on Natural Expressive Speech: Automatic Memorable Spoken Quote Detection F Koto, S Sakti, G Neubig, T Toda, M Adriani… – … Dialog Systems and …, 2015 – Springer … Research related to spoken dialog systems has progressed from the traditional task-based frameworks to more sophisticated social agents (Dautenhahn 2007 … In: Proceedings of NAACHL-HLT, Montréal, Canada, pp 69–77 Bird S (2006) NLTK: the natural language toolkit. … Cited by 1 Related articles All 8 versions

A new Automatic approach for Understanding the Spontaneous Utterance in Human-Machine Dialogue based on Automatic Text Categorization M Lichouri, A Djeradi, R Djeradi – Proceedings of the International …, 2015 – dl.acm.org … The understanding of an ut- terance in SDS (Speech Dialog System) is of a great deal of importance in their generalization, because … de- tection of the boundary of the sentences (Sentence boundary disambiguation)[17],by using ”PUNKT” of NLTK (Natural Language Toolkit) [16 … Related articles

Reformulation Strategies of Repeated References in the Context of Robot Perception Errors in Situated Dialogue N Schutte, J Kelleher, B Mac Namee – 2015 – arrow.dit.ie … The toy black system enables users to interact through a dialog system with a robot that can manipulate objects in a … and Spatial Reasoning The basic natural language processing pipeline of the toy block system involves: (1) parsing the user input (using the NLTK parser [30 … Related articles All 2 versions

Hierarchical neural network generative models for movie dialogues IV Serban, A Sordoni, Y Bengio, A Courville… – arXiv preprint arXiv: …, 2015 – arxiv.org … They showed that an ex- isting dialogue system could successfully be aug- mented with the subtitles, such that, when its re- sponse confidence is … We used the python-based natural language toolkit NLTK (Bird et al., 2009) to perform tokenization and named-entity recognition7. … Cited by 16 Related articles All 4 versions

Using summarization to discover argument facets in online idealogical dialog A Misra, P Anand, JEF Tree, MA Walker – NAACL HLT, 2015 – anthology.aclweb.org … Amita Misra, Pranav Anand, Jean Fox Tree, and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High. … For the verbs category, we ex- cluded the verbs present in the NLTK stop word list. … Cited by 6 Related articles All 7 versions

An Intelligent Natural Language Conversational System for Academic Advising EM Latorre-Navarro, JG Harris – Editorial Preface, 2015 – Citeseer … Keywords—Natural Language Processing; Dialog System; Conversational Agent; Academic Advising; Advising System; Engineering Education; E-learning; Human Computer Interaction INTRODUCTION I. Higher education institutions employ academic advisors to assist … Related articles All 4 versions

Learning task knowledge from dialog and web access V Perera, R Soetens, T Kollar, M Samadi, Y Sun… – Robotics, 2015 – mdpi.com … user. We have created a dialog system able to retrieve information from the Web in real time (ie, while engaged in dialog), which we also consider to be a contribution. In … 14]. For tagging, we use the Python NLTK library [15]. From … Cited by 4 Related articles All 6 versions

Improving Classification of Natural Language Answers to ITS Questions with Item-Specific Supervised Learning. BD Nye, MH Hajeer, Z Cai – FLAIRS Conference, 2015 – pdfs.semanticscholar.org … In this paper, we focus on evaluating the potential benefits of this approach to classifying human input to an ITS dialog system. … Discourse Processes 25(2-3):259–284. Loper, E., and Bird, S. 2002. NLTK: The natural language toolkit. … Related articles All 2 versions

An Improved Method for Detection of Satire from User-Generated Content STOPT Nafis, S Khanna – Citeseer … Recognition of sarcasm may anticipate benefits in many sentiment analysis of NLP applications, such as safe search, review summary reports, engaging dialogue systems and review ranking … Removal of stop words is done using nltk, where English stop words are predefined. …

Simple learning and compositional application of perceptually grounded word meanings for incremental reference resolution C Kennington, D Schlangen – Proceedings of the Conference …, 2015 – anthology.aclweb.org … Words were stemmed using the NLTK (Loper and Bird, 2002) Snowball Stemmer, reducing the 296 … by the assumption that in general, a good rank for the correct object is desirable, even if it doesn’t reach the first position, as when integrated in a dialogue system this information … Cited by 19 Related articles All 8 versions

[BOOK] NLTK essentials N Hardeniya – 2015 – books.google.com … The probabilistic model 67 Speech recognition 68 Text classification 68 Information extraction 70 Question answering systems 70 Dialog systems 71 Word … The Sitemap spider 105 The item pipeline 106 External references 108 Summary 108 Chapter 8: Using NLTK with Other … All 6 versions

Automatic ranking of swear words using word embeddings and pseudo-relevance feedback LF D’Haro, RE Banchs – 2015 Asia-Pacific Signal and …, 2015 – ieeexplore.ieee.org … “IRIS: a chat-oriented dialogue system based on the vector space model.” Proceedings of the ACL 2012 System Demonstrations. … [11] Bird, Steven. “NLTK: the natural language toolkit.” Proceedings of the COLING/ACL on Interactive presentation sessions. … Related articles All 2 versions

Call routing based on a combination of the construction-integration model and latent semantic analysis: A full system G Jorge-Botana, R Olmos, A Barroso – Informatica, 2015 – search.proquest.com … and No Target Domain Data, in Perception in Multimodal Dialog Systems, Proceedings of the 4th IEEE Tutorial and Research Workshop on Perception and Interactive Technologies for Speech-Based Systems … [37] Bird, S. and Loper, E. NLTK: The Natural Language Toolkit. … Cited by 1 Related articles All 13 versions

Building and Applying Perceptually-Grounded Representations of Multimodal Scene Descriptions T Han, C Kennington, D Schlangen – SEMDIAL 2015 goDIAL, 2015 – illc.uva.nl … Applying Perceptually-Grounded Representations of Multimodal Scene Descriptions Ting Han Casey Kennington David Schlangen CITEC/Dialogue Systems Group/Bielefeld … there is a preprocessing step that nor- malises word forms (by stemming them using NLTK (Loper and … Cited by 2 Related articles All 7 versions

Social Media Mining with Natural Language Processing M Abdul-Mageed, M Dickinson – 2015 – scholarworks.iu.edu … conversational agents / dialogue systems ? machine translation … http://www.clearnlp.com ? FreeLing: http://nlp.lsi.upc.edu/freeling/ ? LingPipe: http://alias-i.com/lingpipe/ ? OpenNLP: http://opennlp.apache.org/index.html ? Natural Language Toolkit (NLTK): http://www.nltk …

A comprehensive information extraction module for reducing call handling time in a contact centre KIH Gunathunga, Y Priyadarshana, KKANN Perera… – academia.edu … Abstract- Information extraction plays an important role in text related research and application areas such as text mining and dialogue systems. … III. RESULTS To implement this solution, authors have used python and Natural Language Toolkit (NLTK). … Related articles All 2 versions

A Heuristic Approach to Factoid Question Generation from Sentence A Das, A Shaw, S Sarkar, T Deb – 2015 – academia.edu … Automatic generation of questions is a challenging and an important research area in natural language generation, potentially useful in intelligent tutoring systems, dialogue systems, educational technologies, instructional … “NLTK: the natural language toolkit.” Proceedings of … Related articles

Semeval-2015 task 2: Semantic textual similarity, english, spanish and pilot on interpretability E Agirrea, C Baneab, C Cardiec, D Cerd… – Proceedings of the 9th …, 2015 – aclweb.org … The English subtask com- prised pairs from headlines and image descriptions, and it also introduced new genres, including answer pairs from a tutorial dialogue system and from Q&A websites, and pairs from a dataset tagged with com- mitted belief annotations. … Cited by 70 Related articles All 12 versions

Big Data–Driven Natural Language–Processing Research and Applications V Gudivada, D Rao, V Raghavan – Big Data Analytics, 2015 – books.google.com … 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. … Cited by 6 Related articles

Text Summarization and Speech Synthesis for the Automated Generation of Personalized Audio Presentations S Lawless, P Lavin, M Bayomi, JP Cabral… – … on Applications of …, 2015 – Springer … is a growing demand for increased expressiveness of synthetic speech that is beyond what can be currently produced [12], eg audiobooks, spoken dialogue systems, etc. … Augat, M., Ladlow, M.: An NLTK Package for Lexical-Chain Based Word Sense Disambiguation (2009). 24. … Cited by 1 Related articles All 3 versions

The roles and recognition of haptic-ostensive actions in collaborative multimodal human–human dialogues L Chen, M Javaid, B Di Eugenio, M Žefran – Computer Speech & Language, 2015 – Elsevier … In fact, reference resolution for text is a standard module for many open source NLP toolkits: OpenNLP, 6 NLTK, 7 and GATE. 8. Referring expressions in multimodal dialogue systems are more challenging to resolve, but also richer. … Cited by 4 Related articles All 9 versions

Harnessing context incongruity for sarcasm detection A Joshi, V Sharma… – Proceedings of the 53rd …, 2015 – anthology.aclweb.org … Page 790. References Alias-i. 2008. Lingpipe natural language toolkit. Francesco Barbieri, Horacio Saggion, and Francesco Ronzano. 2014. … 2006. yeah right: sarcasm recognition for spoken dialogue systems. In INTERSPEECH. Oren Tsur, Dmitry Davidov, and Ari Rappoport. … Cited by 16 Related articles All 11 versions

What we talk about when we talk about games: Bottom-up game studies using natural language processing JO Ryan, E Kaltman, M Mateas… – Proc. …, 2015 – pdfs.semanticscholar.org … 2, Eric Kaltman1, Michael Mateas1, and Noah Wardrip-Fruin1 1 Expressive Intelligence Studio 2 Natural Language and Dialogue Systems Lab University … For this step, we used the WordNet lemmatizer [32] available in the Natural Language Toolkit suite of Python modules [7]. … Cited by 7 Related articles All 4 versions

[BOOK] Speech and Language Technology for Language Disorders K Beals, D Dahl, R Fink, M Linebarger – 2015 – books.google.com … 19 Analyzing meaning 19 Information about intermediate structure 24 Converting language to action 25 Limits of current natural language understanding systems 26 Availability of natural-language-processing technology 26 Dialog systems 27 What are dialog systems? … Related articles All 2 versions

Towards universal paraphrastic sentence embeddings J Wieting, M Bansal, K Gimpel, K Livescu – arXiv preprint arXiv: …, 2015 – arxiv.org … development/test splits. To learn the models in this 9Note that we pre-processed the training data with the tokenizer from Stanford CoreNLP (Manning et al., 2014) rather than the included NLTK (Bird et al., 2009) tokenizer. We found that … Cited by 18 Related articles All 2 versions

Development of a Speech Controlled Robot in an Engineering Design Class A Xiao, AS Zhang – ASME 2015 International …, 2015 – … .asmedigitalcollection.asme.org … products and applications, in areas ranging from medical transcription to game control, from call center dialogue systems to information … S. Bird, E. Klein, E. Loper, (2009), Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit, Publisher: O … Related articles

Content-based Tweets Semantic Clustering and Propagation MA Michalakos – 2015 – repository.ihu.edu.gr Page 1. I Content-based Tweets Semantic Clustering and Propagation Marios Aristotelis Michalakos SID: 3301130014 SCHOOL OF SCIENCE & TECHNOLOGY A thesis submitted for the degree of Master of Science (MSc) in Information and Communication Systems … Related articles

Towards Universal Paraphrastic Sentence Embeddings JWMBK Gimpel, K Livescu – arXiv preprint arXiv: …, 2015 – pdfs.semanticscholar.org … 10Note that we pre-processed the training data with the tokenizer from Stanford CoreNLP (Manning et al., 2014) rather than the included NLTK (Bird et al., 2009) tokenizer. We found that doing so significantly im- proves the performance of the skip-thought vectors. … Related articles All 4 versions

[BOOK] Advanced Applications of Natural Language Processing for Performing Information Extraction MJF Rodrigues, AJ da Silva Teixeira – 2015 – Springer … Some of the topics covered in this series include the presentation of real life com- mercial deployment of spoken dialog systems, contemporary methods of speech parameterization, developments in information … 23 2.5.2 Natural Language Toolkit (NLTK) …. … Related articles All 4 versions

Implementing and Evaluating a Scenario Builder Tool for Pediatric Virtual Patients LE Cairco Dukes – 2015 – tigerprints.clemson.edu Page 1. Clemson University TigerPrints All Dissertations Dissertations 5-2015 Implementing and Evaluating a Scenario Builder Tool for Pediatric Virtual Patients Lauren Elizabeth Cairco Dukes Clemson University Follow this … Related articles

Automatic irony-and sarcasm detection in Social media E Forslid, N Wikén – 2015 – diva-portal.org … Example of different tokenizers from the NLTK library can be found on their demo page. 5 … The suffix stripping algorithm used for providing this example is the Porter Stemmer, from the python library NLTK, based on the algorithm developed by Martin Porter [Porter, 1980]. … Related articles

Natural Language Processing for Social Media A Farzindar, D Inkpen – Synthesis Lectures on Human …, 2015 – morganclaypool.com … Semantic Role Labeling Martha Palmer, Daniel Gildea, and Nianwen Xue 2010 Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 Introduction to Chinese Natural Language Processing Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang 2009 … Cited by 6 Related articles All 5 versions

Deep learning approaches to problems in speech recognition, computational chemistry, and natural language text processing GE Dahl – 2015 – tspace.library.utoronto.ca Page 1. Deep learning approaches to problems in speech recognition, computational chemistry, and natural language text processing by George Edward Dahl A thesis submitted in conformity with the requirements for the degree … Cited by 3 Related articles All 5 versions

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent R Amini – 2015 – digitalcommons.fiu.edu … 5.2 Part of speech tags of the Stanford Natural Language Toolkit. . . . . 165 … models employed in most of the current health-related dialogue systems (Discussed in Section 2), toward modeling human’s non-verbal behaviors … Cited by 1 Related articles All 2 versions