Treebank & Dialog Systems 2017


Notes:

A treebank is a parsed text corpus that annotates syntactic or semantic sentence structure.

Wikipedia:

See also:

100 Best Decision Tree Videos | 100 Best TreeMap Videos | AST (Abstract Syntax Tree) & Dialog Systems | Conversation TreesDecision Tree Classifier & Dialog Systems | Grammar Trees & Dialog Systems | Rhetorical Structure TreeStanford Tregex


Utterance selection using discourse relation filter for chat-oriented dialogue systems
A Otsuka, T Hirano, C Miyazaki, R Higashinaka… – Dialogues with Social …, 2017 – Springer
… created a dialogue corpus annotated with Penn Discourse Tree Bank (PDTB)-styled discourse relations [6 … 335–337 (2011)Google Scholar. 9. Shibata, M., Nishiguchi, T., Tomiura, Y.: Dialog system for open … E., Robaldo, L., Joshi, A., Webber, B.: The penn discourse treebank 2.0 …

Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
T Zhao, R Zhao, M Eskenazi – arXiv preprint arXiv:1703.10960, 2017 – arxiv.org
… On the other hand, past research in spo- ken dialog systems and discourse analysis has sug- gested that many linguistic cues capture crucial features in … with past work (Bow- man et al., 2015), we conducted the same lan- guage modelling (LM) task on Penn Treebank us- ing …

Using Summarization to Discover Argument Facets in Online Ideological Dialog
A Misra, P Anand, JEF Tree, M Walker – arXiv preprint arXiv:1709.00662, 2017 – arxiv.org
… Amita Misra, Pranav Anand, Jean Fox Tree, and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N … In the wake of the Penn TreeBank, much progress has been achieved in processing the monologic, informational language characteristic of …

Topic independent identification of agreement and disagreement in social media dialogue
A Misra, M Walker – arXiv preprint arXiv:1709.00661, 2017 – arxiv.org
… Amita Misra & Marilyn A. Walker Natural Language and Dialogue Systems Lab Computer Science Department University of California … that disagreement is subtype of the COMPARISON (CONTRAST) discourse relation, in the Penn Dis- course TreeBank taxonomy, suggesting …

PDTSC 2.0-Spoken Corpus with Rich Multi-layer Structural Annotation
M Mikulová, J Mírovský, A Nedoluzhko, P Pajas… – … Conference on Text …, 2017 – Springer
… closed the gap between the full annotation of the Prague Dependency Treebank (which is … we hope that this resource can help build automatic speech understanding and dialog systems … layers, and will become part of a consolidated Prague Dependency Treebanks release in …

Combining Search with Structured Data to Create a More Engaging User Experience in Open Domain Dialogue
KK Bowden, S Oraby, J Wu, A Misra… – arXiv preprint arXiv …, 2017 – arxiv.org
… [31] R. Prasad, N. Dinesh, A. Lee, E. Miltsakaki, L. Robaldo, A. Joshi, and B. Webber. The penn discourse treebank 2.0 … Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System. Journal of Artificial Intelligence Research, 16:293–319, 2002 …

Dependency Parsing and Dialogue Systems: an investigation of dependency parsing for commercial application
A Adams – 2017 – diva-portal.org
… As such, integrating syntactic information in a dialogue system poses a particular challenge … so as to quantify the differences between this domain and standard English treebank data … specificities of dialogue data through the automatic annotation of in-domain treebanks, as well …

Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders
T Kato, A Nagai, N Noda, R Sumitomo, J Wu… – Proceedings of the 18th …, 2017 – aclweb.org
… 5 Conclusions RAE was applied to utterance intent classification of a smartphone-based Japanese-language spoken dialogue system. To improve the classification ac- curacy, we examined the RAE of multiple AEs un- 63 Page 5 … a sentiment treebank. Proc …

Dependency Parsing and Human-Computer Dialogue
A Adams – 2017 – stp.lingfil.uu.se
… Furthermore, the domain proves challenging in that it differs substantially from that found most Treebanks … parser accuracy on the dataset, and showcasing how dependency syntax can benefit the creation of dialogue systems … (2016), which presents a treebank for English as a …

Learning Generative End-to-end Dialog Systems with Knowledge
T Zhao – 2017 – cs.cmu.edu
… Page 2. November 21, 2017 DRAFT Keywords: dialog systems, end-to-end models, deep learning, reinforcement learn- ing, generative models, transfer learning, zero-shot learning Page 3 … Page 17. November 21, 2017 DRAFT Chapter 2 Related Work 2.1 Dialog Systems …

Miscommunication handling in spoken dialog systems based on error-aware dialog state detection
CH Wu, MH Su, WB Liang – EURASIP Journal on Audio, Speech, and …, 2017 – Springer
… December 2017 , 2017:9 | Cite as. Miscommunication handling in spoken dialog systems based on error-aware dialog state detection … Keywords. Error-aware dialog act Miscommunication Spoken dialog systems. Download fulltext PDF. 1 Introduction …

Novel Methods for Natural Language Generation in Spoken Dialogue Systems
O Dušek – 2017 – dspace.cuni.cz
… Ond?ej Dušek Novel Methods for Natural Language Generation in Spoken Dialogue Systems Institute of Formal and Applied Linguistics Supervisor: Ing … iii Page 4. Page 5. Title: Novel Methods for Natural Language Generation in Spoken Dialogue Systems Author: Ond?ej Dušek …

Deep Reinforcement Learning for Inquiry Dialog Policies with Logical Formula Embeddings
T Hiraoka, M Tsuchida, Y Watanabe – arXiv preprint arXiv:1708.00667, 2017 – arxiv.org
… [10] ——, “An inquiry dialogue system,” Autonomous Agents and Multi-Agent Systems, vol … [17] R. Socher, A. Perelygin, JY Wu, J. Chuang, CD Manning, AY Ng, C. Potts et al., “Recursive deep models for semantic compositionality over a sentiment treebank,” in Proceedings of …

Incremental Dialogue Act Recognition: token-vs chunk-based classification
E Ebhotemhen, V Petukhova, D Klakow – inform, 2017 – pdfs.semanticscholar.org
… of-speech (POS) tags, n-grams of POS tags using Penn Tree Bank parser [20 … bata, “Understanding unsegmented user utterances in real-time spoken dialogue systems,” in Proceedings … Building a large annotated corpus of english: The penn treebank,” Computational linguistics …

Semantic Comprehension System for F-2 Emotional Robot
A Kotov, N Arinkin, A Filatov, L Zaidelman… – First International Early …, 2017 – Springer
… researchers often use the bag-of-n-grams – an unordered set of tuples consisting of n consecutive words [2, 6]. Dialogue systems also often … Application of each rule is evaluated, scores are calculated on the basis of SynTagRus treebank [16] – total score is calculated for a stack …

RSL17BD at DBDC3: Computing Utterance Similarities based on Term Frequency and Word Embedding Vectors
S Kato, T Sakai – workshop.colips.org
… tokenize.html# module-nltk.tokenize.punkt 3http://www.nltk.org/api/nltk.tokenize.html# module-nltk.tokenize.treebank 4http://www … Tsunomori, T. Taka- hashi, and N. Kaji, “Overview of dialogue breakdown detection challenge 3,” in Proceedings of Dialog System Technology …

Foreword to the Special Issue on Uralic Languages
TA Pirinen, HZ für Sprachkorpora, T Trosterud… – 2017 – nejlt.ep.liu.se
… We also endorse researchers to work on treebanks and similar resources to increase visi- bility of the minority Uralic languages within the international research community … The szeged treebank. In Václav et al … Constraint grammar in dialogue systems …

Towards an Arabic-English Machine-Translation Based on Semantic Web
NA Dahan, FM Ba-Alwi, IA Al-Baltah… – arXiv preprint arXiv …, 2017 – arxiv.org
… In addition, according to Green, et al [16], their parser was similar to another Treebank in gross statistical terms, annotation consistency … the Portuguese-English MT was to provide an efficient way to process the homographs [6]. And where the last dialog systems were depending …

Towards an Arabic-English Machine-Translation Based on Semantic Web
FM Ba-Alwi, IA Al-Baltah, GH Al-gapheri – researchgate.net
… In addition, according to Green, et al [16], their parser was similar to another Treebank in gross statistical terms, annotation consistency … the Portuguese-English MT was to provide an efficient way to process the homographs [6]. And where the last dialog systems were depending …

A demo of FORGe: the Pompeu Fabra Open Rule-based Generator
S Mille, L Wanner – Proceedings of the 10th International Conference on …, 2017 – aclweb.org
… The current generator has been mainly developed for English on the dependency Penn Treebank (Johansson and Nugues, 2007 … as Spanish, German French, and Polish, in the context of ontology-to-text generation as part of a dialogue system … From Tree- Bank to PropBank …

A Complete Bibliography of ACM Transactions on Speech and Language Processing (TSLP)
NHF Beebe – 2017 – tug.ctan.org
… transformation [VK05]. translation [FB05, SPF+12, SWY13, TZ07, WS06, ZYS08]. treebank [YBKR07]. treebanks [CLS13b]. turn [RE12] … Page 7. REFERENCES 7 to evaluate parsing difficulty across treebanks … Evaluating dis- course understanding in spoken dialogue systems …

Dialogue Act Annotation with the ISO 24617-2 Standard
H Bunt, V Petukhova, D Traum… – Multimodal Interaction with …, 2017 – Springer
This chapter describes recent and ongoing annotation efforts using the ISO 24617-2 standard for dialogue act annotation. Experimental studies are reported on the annotation by human annotators and by.

Can Discourse Relations be Identified Incrementally?
F Yung, H Noji, Y Matsumoto – Proceedings of the Eighth International …, 2017 – aclweb.org
… On top of generating more natural and timely response in dialogue systems and im- proving language … of an- notation of discourse signals over the RST Dis- course Treebank (Carlson et al … In the RST Discourse Tree- bank, a DR is annotated between two consecu- tive discourse …

Input-to-Output Gate to Improve RNN Language Models
S Takase, J Suzuki, M Nagata – arXiv preprint arXiv:1709.08907, 2017 – arxiv.org
… 1993. Building a Large Anno- tated Corpus of English: The Penn Treebank. Com- putational Linguistics 19(2):313–330 … 2015. Se- mantically Conditioned LSTM-based Natural Lan- guage Generation for Spoken Dialogue Systems …

TrumpBot: Seq2Seq with Pointer Sentinel Model
F Zivkovic, D Chen – pdfs.semanticscholar.org
… Models [16] is a recent, clever, and simple method which produces state-of- the-art perplexity scores on Penn Tree Bank and Wiki … that most traditional measures of NLP tasks, such as BLEU score, ROGUE and METEOR are unsuitable measures of dialog systems because most …

A practical guide to sentiment analysis
E Cambria, D Das, S Bandyopadhyay, A Feraco – 2017 – Springer
… Examples of the second domain will include, but not limited to: computational and psychological models of emotions, bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning …

Generating sentence planning variations for story telling
SM Lukin, LI Reed, MA Walker – arXiv preprint arXiv:1708.08580, 2017 – arxiv.org
… Previous research on NLG of linguistic style shows that dialogue systems are more effective if they can generate stylistic linguistic variations based on … clauses re- lated by the contingency discourse relation (one of many listed in the Penn Discourse Tree Bank (PDTB) (Prasad et …

Multiple-Weight Recurrent Neural Networks
Z Cao, L Wang, G De Melo – Proceedings of the 26th International Joint …, 2017 – ijcai.org
… For dialogue systems, contextual information and dialogue interactions be- tween speakers are important signals … 4.1 Language Modeling We use the standard Penn Treebank dataset [Marcus et al., 1993] for language modeling …

Learning lexico-functional patterns for first-person affect
L Reed, J Wu, S Oraby, P Anand, M Walker – arXiv preprint arXiv …, 2017 – arxiv.org
… This provides 67,710 additional phrases, includ- ing 58,972 positive phrases and 8,738 negative phrases. The retrained model includes both the labels from the original Sentiment Treebank and Page 4 … 2017. Data-driven dialogue systems for social agents …

A Bridge from the Use-Mention Distinction to Natural Language Processing
S Wilson – The Semantics and Pragmatics of Quotation, 2017 – Springer
… Designing and evaluating an adaptive spoken dialogue system. User Modeling and User-Adapted Interaction, 12, 111–137.CrossRefGoogle Scholar. Lynch, M. (2001) … Building a large annotated corpus of English: The Penn Treebank …

Automatic Prediction of Discourse Connectives
E Malmi, D Pighin, S Krause, M Kozhevnikov – arXiv preprint arXiv …, 2017 – arxiv.org
… ranging from summarization, to text simplification, to answer synthesis and conversationalization for dialog systems … used dataset for computa- tional discourse studies is the Penn Discourse Treebank (PDTB) (Prasad … This tree- bank is based on a set of 2 159 Wall Street Journal …

Predicting Users’ Negative Feedbacks in Multi-Turn Human-Computer Dialogues
X Wang, J Wang, Y Liu, X Wang, Z Wang… – Proceedings of the Eighth …, 2017 – aclweb.org
… wangbaoxun}@trio.ai Abstract User experience is essential for human- computer dialogue systems. However, it is impractical to ask users to provide explicit feedbacks when the agents’ responses dis- please them. Therefore, in …

Joint, incremental disfluency detection and utterance segmentation from speech
J Hough, D Schlangen – Proceedings of the 15th Conference of the …, 2017 – aclweb.org
… Julian Hough and David Schlangen Dialogue Systems Group // CITEC // Faculty of Linguistics and Literature Bielefeld University firstname.lastname@uni-bielefeld … data for disflu- ency detection (all conversation numbers begin- ning sw2*,sw3* in the Penn Treebank III release …

Generative Neural Machine for Tree Structures
G Zhou, P Luo, R Cao, Y Xiao, F Lin, B Chen… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Generative Neural Machine for Tree Structures Ganbin Zhou1,2, Ping Luo1, Rongyu Cao1,2, Yijun Xiao3, Fen Lin3, Bo Chen3, Qing He1 1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences …

COMPUTATIONAL LINGUISTICS AND RESEARCHES ABOUT UYGHUR LANGUAGE
M ORHUN – COMPUTATIONAL LINGUISTICS, 2017 – pdfs.semanticscholar.org
… For example, content management of a text, information retrieval, dialog systems, document clustering … based in the same tags that used in Turkish Treebank corpora (Atalay … ABEILLE Anne (2003), “Treebanks: Building and Using Parsed Corpora”, Dordrecht: Kluwer Academic …

Unsupervised induction of contingent event pairs from film scenes
Z Hu, E Rahimtoroghi, L Munishkina… – arXiv preprint arXiv …, 2017 – arxiv.org
… Zhichao Hu, Elahe Rahimtoroghi, Larissa Munishkina, Reid Swanson and Marilyn A. Walker Natural Language and Dialogue Systems Lab Department of … a broad range of per- spectives: (1) as inference of a discourse relations (eg the Penn Discourse Treebank (PDTB) CON …

Boosting a Rule-Based Chatbot Using Statistics and User Satisfaction Ratings
O Efraim, V Maraev, J Rodrigues – Conference on Artificial Intelligence …, 2017 – Springer
… Seddah, D., Sagot, B., Candito, M., Mouilleron, V., Combet, V.: The French Social Media Bank: a treebank of noisy user generated … Walker, M., Langkilde, I., Wright, J., Gorin, A., Litman, D.: Learning to predict problematic situations in a spoken dialogue system: experiments with …

Semantic specialisation of distributional word vector spaces using monolingual and cross-lingual constraints
N Mrkši?, I Vuli?, DÓ Séaghdha, I Leviant… – arXiv preprint arXiv …, 2017 – arxiv.org
… in each case outperforming the monolin- gual model. To the best of our knowledge, this is the first work on multilingual training of any compo- nent of a statistical dialogue system. Our results in- dicate that multilingual training …

Systemic functional linguistics and computation: New directions, new challenges
J Bateman, D McDonald, T Hiippala… – … Handbook of Systemic …, 2017 – helsinki.fi
… algorithms for their processing, as well as substantial computationally accessible re- sources such as corpora, treebanks (ie, grammatically … This included both Terry Winograd’s SHRDLU (Winograd 1972), a land- mark natural language dialogue system that demonstrated that …

Non-Contextual Modeling of Sarcasm using a Neural Network Benchmark
ND Radpour, V Ashokkumar – arXiv preprint arXiv:1711.07404, 2017 – arxiv.org
… extensive task, it can be extended via the same method that we present to capture different forms of nuances in communication and making for much more natural and engaging dialogue systems … Recursive deep models for semantic compositionality over a sentiment treebank …

A Part-of-Speech Enhanced Neural Conversation Model
C Luo, W Li, Q Chen, Y He – European Conference on Information …, 2017 – Springer
… Our POS tag set is the LDC Chinese Treebank POS tag set that is used in the Stanford Chinese taggers … 1577–1586 (2015)Google Scholar. 5. Serban, IV, Sordoni, A., Bengio, Y., Courville, A., Pineau, J.: Building end-to-end dialogue systems using generative hierarchical neural …

Understanding Task Design Trade-offs in Crowdsourced Paraphrase Collection
Y Jiang, JK Kummerfeld, WS Laseck – arXiv preprint arXiv:1704.05753, 2017 – arxiv.org
… US geogra- phy (GEOQUERY Tang and Mooney, 2001), text from the Wall Street Journal section of the Penn Treebank (WSJ Marcus et … Building a large an- notated corpus of English: The Penn Tree- bank … Crowdsourcing language genera- tion templates for dialogue systems …

Using Past Speaker Behavior to Better Predict Turn Transitions
M Tomer – 2017 – digitalcommons.ohsu.edu
… in spoken dialogue systems. 2.1 Human-Human Conversations … speakers. The original audio recordings were later annotated and was released as part of the Penn Treebank 3 corpus, which included 650 annotated conversations. The current release used for this …

Synthesising uncertainty: the interplay of vocal effort and hesitation disfluencies
E Székely, J Mendelson, J Gustafson – 18th Annual Conference of …, 2017 – isca-speech.org
… For example, in light of these findings, we can imply that if an incremental dialogue system inserts filled pauses to buy time, it can slightly increase its … [34] R. Socher, A. Perelygin, and J. Wu, “Recursive deep models for semantic compositionality over a sentiment treebank,” Proc …

Native Language Identification of Spoken Language Using Recurrent Neural Networks
KC Huang, J Lu, W Lu – stanford.edu
… The main application for the system was a spoken dialogue system giving information about venues in San Francisco across two domains about … we use the Python Natural Language Toolkit (NLTK) to automatically ap- ply part-of-speech tags with the Penn Treebank Tagset …

Maximum-likelihood augmented discrete generative adversarial networks
T Che, Y Li, R Zhang, RD Hjelm, W Li, Y Song… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Maximum-Likelihood Augmented Discrete Generative Adversarial Networks Tong Che * 1 Yanran Li * 2 Ruixiang Zhang * 3 R Devon Hjelm 1 4 Wenjie Li 2 Yangqiu Song 3 Yoshua Bengio 1 Abstract Despite the successes …

Effective Spoken Language Labeling with Deep Recurrent Neural Networks
M Dinarelli, Y Dupont, I Tellier – arXiv preprint arXiv:1706.06896, 2017 – arxiv.org
… This is a very important feature in spoken dialog systems, as the correct in- terpretation of a dialog turn may depend on the information extracted from … 1Since we don’t have a graphic card, our networks are still rela- tively expensive to train on corpora like the Penn Treebank …

Non-Contextual Modeling of Sarcasm using a Neural Network Benchmark
V Ashokkumar, ND Radpour – 2017 – ttic.edu
… Abstract One of the most crucial components of natural human-robot interaction is artificial intuition and its influence on dialog systems … 2013. Recursive deep mod- els for semantic compositionality over a sentiment treebank …

Domain-Adaptable Hybrid Generation of RDF Entity Descriptions
O Biran, K McKeown – Proceedings of the Eighth International Joint …, 2017 – aclweb.org
… own, 2015). The model provides prior and transi- tion probabilities for the four top-level Penn Dis- course TreeBank (PDTB) (Prasad et al., 2008) dis- course relations: expansion, comparison, contin- gency and temporal. These …

Controllable text generation
Z Hu, Z Yang, X Liang, R Salakhutdinov… – arXiv preprint arXiv …, 2017 – arxiv.org
… To control the sentiment (“positive” or “neg- ative”) of generated sentences, we test on the following la- beled sentiment data: (1) Stanford Sentiment Treebank-2 (SST-full) (Socher et al., 2013) consists of 6920/872/1821 movie review sentences with binary sentiment annotations …

Deep reinforcement learning: An overview
Y Li – arXiv preprint arXiv:1701.07274, 2017 – arxiv.org
… Then we discuss various applications of RL, including games, in particular, AlphaGo, robotics, spoken dialogue systems (aka chatbot), machine translation, text sequence prediction, neural architecture design, personalized web services, healthcare, finance, and music …

Proceedings of the Workshop on Logic and Algorithms in Computational Linguistics 2017 (LACompLing2017)
R Loukanova, K Liefke – Workshop on Logic and Algorithms in …, 2017 – diva-portal.org
… di- alogue systems, language and cognition, pragmatics, formal semantics, semantic coordination, in-vehicle dialogue systems, philosophy of … Dependencies Abstract: Universal Dependencies (UD) is a framework for cross-linguis- tically consistent treebank annotation that has …

Parsing and beyond: Tools and resources for Estonian
K Muischnek, K Müürisep… – Acta Linguistica …, 2017 – akademiai.com
… for a wide range of languages, in- cluding languages with inflectional morphology and relatively small tree- banks (for example … 7. Corpora and treebanks … We succeeded in getting funding for the creation of an Estonian Dependency Treebank, and completed its first version by …

Toward controlled generation of text
Z Hu, Z Yang, X Liang… – International …, 2017 – proceedings.mlr.press
… or “neg- ative”) of generated sentences, we test on the following la- beled sentiment data: (1) Stanford Sentiment Treebank-2 (SST … in- corporate prior knowledge or human intentions (Hu et al., 2016a;b); or plug the disentangled generation model into dialog systems to generate …

Variational Autoencoder for Semi-Supervised Text Classification.
W Xu, H Sun, C Deng, Y Tan – AAAI, 2017 – aaai.org
Page 1. Variational Autoencoder for Semi-Supervised Text Classification Weidi Xu, Haoze Sun, Chao Deng, Ying Tan Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer …

AppTechMiner: Mining Applications and Techniques from Scientific Articles
M Singh, S Dan, S Agarwal, P Goyal… – Proceedings of the 6th …, 2017 – dl.acm.org
… Word Alignment, Conditional Random Fields, Maximum Entropy, Coreference Resolution, Machine Learning, Dialogue Systems, Textual Entailment … Penn Treebank, Stanford Parser, Rate Training, Berkeley Parser, Machine Translation, Statistical Machine Translation, Charniak …

Label-dependencies aware recurrent neural networks
Y Dupont, M Dinarelli, I Tellier – arXiv preprint arXiv:1706.01740, 2017 – arxiv.org
… Since evaluations on tasks like POS tagging on the Penn Treebank are basically reaching perfection (state-of-the-art is at 97.55 … The ATIS corpus (Air Travel Information System) [26] was collected for building a spoken dialog system able to provide flight information in the United …

Shallow PARsing and Knowledge extraction for Language Engineering
I Annex – cogsci.ed.ac.uk
… Speech dialogue systems will soon be in the position of providing services such as … words of manually parsed material (Lancaster Treebank, Susanne corpus, Penn Treebank, tosca database … In recent attempts to manually construct large `treebanks’ of parsed texts, canonical …

Speech Intention Classification with Multimodal Deep Learning
Y Gu, X Li, S Chen, J Zhang, I Marsic – Canadian Conference on Artificial …, 2017 – Springer
… 7. Williams, JD, Kamal, E., Ashour, M., Amr, H., Miller, J., Zweig, G.: Fast and easy language understanding for dialog systems with Microsoft … A., Wu, JY, Chuang, J., Manning, CD, Ng, AY, Potts, C.: Recursive deep models for semantic compositionality over a sentiment TreeBank …

Recent trends in deep learning based natural language processing
T Young, D Hazarika, S Poria, E Cambria – arXiv preprint arXiv …, 2017 – arxiv.org
… White, 2014). NLP enables computers to perform a wide range of natural language related tasks at all levels, ranging from parsing and part-of-speech (POS) tagging, to machine translation and dialog systems. Deep learning …

Natural Language Processing: State of The Art, Current Trends and Challenges
D Khurana, A Koli, K Khatter, S Singh – arXiv preprint arXiv:1708.05148, 2017 – arxiv.org
… The most procedures for part of speech can work efficiently on European languages, but it won’t on Asian languages or middle eastern languages. Sanskrit part of speech tagger is specifically uses treebank technique … (Fang et al. 2015 [72]) 6.6 Dialogue System …

Natural language understanding and communication for human-robot collaboration
MI Bloch – ipvs.informatik.uni-stuttgart.de
… Universal Dependencies (UD) is a multilingual treebank collection [Niv+16] … Considering autonomously working robots with planning abilities, a dialog system makes these robots to co-workers instead of subordinates, as a dialog system enables these robots to suggest tasks …

A Thematicity-based prosody enrichment tool for CTS
M Domínguez Bajo, M Farrús… – Proceedings of the 18th …, 2017 – repositori.upf.edu
… Korbayová, S. Ericsson, KJ Rodr?guez, and E. Kara- grjosova, “Producing Contextually Appropriate Intonation in an Information-State Based Dialogue System,” in Proceedings of … [9] B. Bohnet, A. Burga, and L. Wanner, “Towards the annotation of penn treebank with information …

Remembering a Conversation–A Conversational Memory Architecture for Embodied Conversational Agents
M Elvir, AJ Gonzalez, C Walls, B Wilder – Journal of Intelligent …, 2017 – degruyter.com
Jump to ContentJump to Main Navigation …

Revisiting Activation Regularization for Language RNNs
S Merity, B McCann, R Socher – arXiv preprint arXiv:1708.01009, 2017 – arxiv.org
… 13M 83.9 81.1 Table 6. Single model perplexity results over the Penn Treebank for tanh RNN and GRU … Semanti- cally Conditioned LSTM-based Natural Language Gen- eration for Spoken Dialogue Systems. arXiv preprint arXiv:1508.01745, 2015 …

A deep reinforcement learning chatbot
IV Serban, C Sankar, M Germain, S Zhang… – arXiv preprint arXiv …, 2017 – arxiv.org
… 1 Introduction Dialogue systems and conversational agents – including chatbots, personal assistants and voice- control interfaces – are becoming ubiquitous in modern society … 2 System Overview Early work on dialogue systems (Weizenbaum 1966, Colby 1981, Aust et al …

Towards a top-down policy engineering framework for attribute-based access control
M Narouei, H Khanpour, H Takabi, N Parde… – Proceedings of the …, 2017 – dl.acm.org
… 4.2 Recurrent Neural Network (RNN) Sentence Classi er Recently, DNNs have been used with increasing frequency in a variety of text processing applications, from sentiment analysis [41] to conversational text processing for dialogue systems [22, 48]. Collobert et al …

Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold
S Swayamdipta, S Thomson, C Dyer… – arXiv preprint arXiv …, 2017 – arxiv.org
… We then introduce a method that uses phrase- syntactic annotations from the Penn Tree- bank during training only, through a mul- titask objective; no … This task is trained on the Penn Treebank, sharing the underlying sentence representation with the frame-semantic parser …

EXTRACTING NAMED ENTITIES AND RELATIONS FROM SPEECH
U Seema – 2017 – academicscience.co.in
… Relation Extraction can be effectively applied in the field of machine translation, information extraction, text summarization and dialogue systems … This pipeline consists of a high performance Penn Treebank- compliant tokenizer, close to state-of-art part-of-speech (POS) tagger …

Adversarial generation of natural language
S Rajeswar, S Subramanian, F Dutil, C Pal… – arXiv preprint arXiv …, 2017 – arxiv.org
… They can also be learned via grammar in- duction (Brill, 1993) on large treebanks of natural language and so the data generating distribution is not synthetic as in (Yu et al … Generating language that belongs to a toy CFG and an induced PCFG from the Penn Treebank (Marcus …

Telugu dependency parsing using different statistical parsers
BVS Kumari, RR Rao – Journal of King Saud University-Computer and …, 2017 – Elsevier
… Parsing is useful in major NLP applications like Machine Translation, Dialogue Systems, Question Answering … The availability of phrase structure treebank for English (Marcus et al., 1993) has … Due to the availability of dependency treebanks, there are several recent attempts at …

CCG Supertagging via Bidirectional LSTM-CRF Neural Architecture
R Kadari, Y Zhang, W Zhang, T Liu – Neurocomputing, 2017 – Elsevier
… network. 4.1. Datasets. We used the most common data set used for parsing studies, the English version of the CCGBank corpus; a CCG derivation tree corpus created from the Penn Treebank by Hockenmaier and Steedman [15] …

Sarcasm Detection Using Sentiment Flow Shifts
E Filatova – 2017 – pdfs.semanticscholar.org
… for se- mantic compositionality over a sentiment treebank. In Proceed- ings of EMNLP, 1631–1642. Stroudsburg, PA: Association for Computational Linguistics. Tepperman, J.; Traum, D.; and Narayanan, SS 2006. “yeah right”: Sarcasm recognition for spoken dialogue systems …

A knowledge and reasoning toolkit for cognitive applications
M Canim, C Cornelio, R Farrell, A Fokoue… – Proceedings of the fifth …, 2017 – dl.acm.org
… art neural network parsers (eg, [76], [3]) can achieve high accuracy on parsed corpora benchmarks such as the Penn Treebank [55] … Ultimately, a question answering system or dialogue system should be able to query the resulting graph to answer ques- tions involving temporal …

Do neural nets learn statistical laws behind natural language?
S Takahashi, K Tanaka-Ishii – PloS one, 2017 – journals.plos.org
… The Penn Treebank dataset which we also used is accessible from Linguistic Data … processing tasks such as machine translation [1], text summarization [2], dialogue systems [3], and … 3 show results obtained using The Wall Street Journal (from the Penn Tree Bank Dataset) and …

Interpreting and extracting open knowledge for human-robot interaction
D Lu, X Chen – IEEE/CAA Journal of Automatica Sinica, 2017 – ieeexplore.ieee.org
Page 1. 686 IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 4, NO. 4, OCTOBER 2017 Interpreting and Extracting Open Knowledge for Human-Robot Interaction Dongcai Lu and Xiaoping Chen Abstract—A more natural …

Syntax and Semantics Question Analysis Using User Modelling and Relevance Feedback
A Saany, I Syarilla, A Mamat, A Mustapha… – … Journal on Advanced …, 2017 – media.neliti.com
… 8, point-11) The part-of-speech name abbreviations are based on the Penn Treebank tag set for English taggers. The parsed result of the user’s NL question also includes the Stanford typed dependencies. The Stanford Typed …

Real-time natural language corrections for assistive robotic manipulators
A Broad, J Arkin, N Ratliff, T Howard… – … International Journal of …, 2017 – journals.sagepub.com
We propose a generalizable natural language interface that allows users to provide corrective instructions to an assistive robotic manipulator in real-time. Thi…

Graph Enhanced Memory Networks for Sentiment Analysis
Z Xu, R Vial, K Kersting – Joint European Conference on Machine Learning …, 2017 – Springer
… In many cases, there exists complicated relational structure in the data, by which the memories can be linked together into graphs to propagate information. Typical examples include tree structure of a sentence and knowledge graph in a dialogue system …

Sequence Modeling with Hierarchical Deep Generative Models with Dual Memory
Y Zheng, L Wen, J Wang, J Yan, L Ji – Proceedings of the 2017 ACM on …, 2017 – dl.acm.org
… which act as central tasks towards multiple applications related to language understanding, such as machine translation [2, 7], dialogue system [35, 36 … We first perform language modeling task on Penn Treebank Dataset (PTB) [24] and WikiText-2 Dataset (WT-2) [21], comparing …

Adversarial generation of natural language
S Subramanian, S Rajeswar, F Dutil, C Pal… – Proceedings of the 2nd …, 2017 – aclweb.org
… can also be learned via grammar in- duction (Brill, 1993) on large treebanks of natural … objectives produce realistic sentences on datasets of varying complexity (CMU-SE, Penn Treebank and the … GANs in other domains of NLP such as non goal-oriented dialog systems where a …

A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models
K Goyal, G Neubig, C Dyer… – arXiv preprint arXiv …, 2017 – arxiv.org
… [6] IV Serban, A. Sordoni, Y. Bengio, A. Courville, and J. Pineau, “Building end-to-end dialogue systems using generative hierarchical neural network … [28] J. Hockenmaier and M. Steedman, “Acquiring compact lexicalized grammars from a cleaner treebank.,” in LREC, 2002 …

Deep Speech Recognition
L Deng – microsoft.com
Page 1. Deep Speech Recognition New-Generation Models & Methodology for Advancing Speech Technology and Information Processing Li Deng Microsoft Research, Redmond, USA IEEE ChinaSIP Summer School, July 6, 2013 …

QUESTION ANSWERING SYSTEM: A REVIEW ON QUESTION ANALYSIS, DOCUMENT PROCESSING, AND ANSWER EXTRACTION TECHNIQUES.
FS UTOMO, N SURYANA… – Journal of Theoretical & …, 2017 – search.ebscohost.com
Page 1. Journal of Theoretical and Applied Information Technology 31st July 2017. Vol.95. No 14 © 2005 – ongoing JATIT & LLS ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 3158 QUESTION ANSWERING SYSTEM : A REVIEW ON …

Distinguishing between facts and opinions for sentiment analysis: Survey and challenges
I Chaturvedi, E Cambria, RE Welsch, F Herrera – Information Fusion, 2017 – Elsevier
… leading to many exciting open challenges, as well as in the business world, due to the remarkable benefits to be had from financial [29] and political [30] forecasting, e-health [31] and e-tourism [32], human communication comprehension [33] and dialogue systems [34], etc …

Sequential short-text classification with neural networks
F Dernoncourt – 2017 – dspace.mit.edu
Page 1. Sequential Short-Text Classification MAOT ITUTEl OF TECHNQLOGY with Neural Networks JUN 23 201 by Franck Dernoncourt ARCHiVES Submitted to the Department of Electrical Engineering and Computer Science …

Incremental Tree Substitution Grammar for Parsing and Sentence Prediction
F Sangati, F Keller – research.ed.ac.uk
… 2002), machine translation (Schwartz et al., 2011; Tan et al., 2011), reading time modeling (Demberg and Keller, 2008), or dialogue systems (Stoness et … is composed of (i) a set of arbitrarily large fragments, usually ex- tracted from an annotated phrase-structure treebank, and (ii …

Transition-Based Technique for Syntactic Linearization and Deep Input Linearization
RS Puduppully – 2017 – web2py.iiit.ac.in
Page 1. Transition-Based Technique for Syntactic Linearization and Deep Input Linearization Thesis submitted in partial fulfillment of the requirements for the degree of MS by Research in Computer Science by Ratish Surendran Puduppully 201407662 …

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
M Palmer, R Hwa, S Riedel – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
Page 1. EMNLP 2017 The Conference on Empirical Methods in Natural Language Processing Proceedings of the Conference September 9-11, 2017 Copenhagen, Denmark Page 2. c?2017 The Association for Computational Linguistics …

Automatic question generation for virtual humans
EL Fasya – 2017 – essay.utwente.nl
… question. Figure 2.4 illustrates a simple finite-state automation architecture of a dialogue manager in a spoken dialogue system [2] … tokenize, and parse input texts resulting in a Penn Treebank structure (eg Alice = NNP, watched = VBD, the = DT, white = NNP, rabbit = NNP) …

Constructing Sentences from Text Fragments: Aggregation in Text-to-text Generation
V Chenal – 2017 – digitool.library.mcgill.ca
… NP NNP Vinken NNP Pierre Figure 3.1: Example of constituent tree from the Penn Treebank Wall Street Journal corpus (Marcus, Marcinkiewicz, and Santorini 1993) unlabeled … The datasets used for our task are extracted from the Penn Treebank Wall Street Journal …

Learning Algorithms for Broad-Coverage Semantic Parsing
S Swayamdipta – 2017 – cs.cmu.edu
… end architecture. The second ap- proach uses a multi-task learning architecture to learn semantic graphs and only a few relevant syntactic substructures from Penn Treebank which are likely to help in learning the former. Both …

Community Standards for Linguistically-Annotated Resources
N Ide, N Calzolari, J Eckle-Kohler, D Gibbon… – Handbook of Linguistic …, 2017 – Springer
This chapter provides a broad overview of the state-of-the-art in standards development for language resources, beginning with a brief historical overview to serve as context. It describes in some det.

Inference of Fine-Grained Event Causality from Blogs and Films
Z Hu, E Rahimtoroghi, MA Walker – arXiv preprint arXiv:1708.09453, 2017 – arxiv.org
… Zhichao Hu, Elahe Rahimtoroghi and Marilyn A Walker Natural Language and Dialogue Systems Lab Department of Computer Science, University of … This work ex- plicitly links their definitions to research using the Penn Discourse Treebank (PDTB) definition of CONTINGENCY …

Challenges in sentiment analysis
SM Mohammad – A Practical Guide to Sentiment Analysis, 2017 – Springer
… 2003), detecting happiness and well-being (Schwartz et al. 2013), tracking the stock market (Bollen et al. 2011), and improving automatic dialogue systems (Velásquez 1997; Ravaja et al. 2006). The sheer volume of work in this area precludes detailed summarization here …

Inferring Narrative Causality between Event Pairs in Films
Z Hu, MA Walker – arXiv preprint arXiv:1708.09496, 2017 – arxiv.org
… Zhichao Hu and Marilyn A. Walker Natural Language and Dialogue Systems Lab Department of Computer Science, University of California Santa Cruz Santa Cruz, CA 95064, USA zhu@soe.ucsc.edu, mawalker@ucsc.edu Abstract …

Painting Pictures with Words-From Theory to System
R Coyne – 2017 – search.proquest.com
… PAR allows instructions such as if you agree to go for a walk with someone, then follow them to be given and then triggered in the future. Ulysse [Godreaux et al., 1999] is an interactive spoken dialog system used to navigate in virtual worlds …

Text Generation Based on Generative Adversarial Nets with Latent Variable
H Wang, Z Qin, T Wan – arXiv preprint arXiv:1712.00170, 2017 – arxiv.org
… It is also essential to machine translation, text summarization, question answering and dialogue system [1]. One popular ap- proach for text … Marcus, Mitchell P and Marcinkiewicz, Mary Ann and Santorini, Beatrice: Building a large annotated corpus of english: the penn treebank …

Multiple relations extraction among multiple entities in unstructured text
J Liu, H Ren, M Wu, J Wang, H Kim – Soft Computing, 2017 – Springer
… among entities, mine latent relations among entities, and perform other complex NLP work such as spoken dialog systems and conversational … In 2000, a lexicalization probabilistic syntax model was proposed, which is trained by Penn TreeBank, and achieved good results in …

Slim Embedding Layers for Recurrent Neural Language Models
Z Li, R Kulhanek, S Wang, Y Zhao, S Wu – arXiv preprint arXiv:1711.09873, 2017 – arxiv.org
… with different ratio (SE). The first case is the uncompressed model that uses the same number of hidden states and uses the same full softmax layer and has much larger number of parameters. We first report the results on Penn Treebank (PTB) dataset …

Disfluency Detection using a Noisy Channel Model and a Deep Neural Language Model
PJ Lou, M Johnson – Proceedings of the 55th Annual Meeting of the …, 2017 – aclweb.org
… Moreover, disfluen- cies pose a major challenge to natural language processing tasks, such as dialogue systems, that rely on speech transcripts … Training a parsing-based model requires large an- notated tree-banks that contain both disfluencies and syntactic structures …

A Complete Bibliography of ACM Transactions on Asian Language Information Processing
NHF Beebe – 2017 – tug.ctan.org
… Tree [126, 175, 178]. Treebank [172]. Treebanks [172]. triggers [44]. TRUES [123] … Resolution of referring expressions in a Korean multimodal dialogue system. ACM Transactions on Asian Lan- guage Information Processing, 2(4):324–337, December 2003. CODEN …

Ethical by Design: Ethics Best Practices for Natural Language Processing
JL Leidner, V Plachouras – Proceedings of the First ACL Workshop on …, 2017 – aclweb.org
… lead to ethical questions around privacy9: Corpora such as the British National Corpus, the Collins COBUILD corpus or the Penn Treebank contain names of … Picture a spoken dialog system that is easy to use for a young male financial professional user with a Lon- don English …

Dynamic ontology for service robots
S Kanjaruek – 2017 – uobrep.aws.openrepository.com
… 45 Figure 3.2 Example of labels of physical object 50 Figure 3.3 Example of text file 51 Figure 3.4 Results using Brown and Penn Treebank tags 52 Figure 3.5 Text file sends to the Automatic Ontology process 53 Figure 3.6 The Automatic Ontology process 55 …

Variational Reasoning for Question Answering with Knowledge Graph
Y Zhang, H Dai, Z Kozareva, AJ Smola… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Variational Reasoning for Question Answering with Knowledge Graph Yuyu Zhang1? , Hanjun Dai1? , Zornitsa Kozareva2, Alexander J. Smola2, and Le Song1 1College of Computing, Georgia Institute of Technology …

Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
S Poria, H Peng, A Hussain, N Howard, E Cambria – Neurocomputing, 2017 – Elsevier
Skip to main content …

Learning Semantic Patterns for Question Generation and Question Answering
HP Rodrigues – 2017 – pdfs.semanticscholar.org
… This approach of learning by analogy, or example-based systems [Aamodt and Plaza, 1994], has also been applied in other domains, such as in creation of dialog systems [Nio et al., 2014] or translation of unknown words [Langlais and Patry, 2007] …

Error Analysis in an Automated Narrative Information Extraction Pipeline
J Valls-Vargas, J Zhu, S Ontanon – IEEE Transactions on …, 2017 – ieeexplore.ieee.org
… Fig. 1. Parse tree annotated by Voz after the mention extraction process. Margaretha & DeVault [37] tackle the issue of automated eval- uation of pipeline architectures in natural language dialogue systems using a Wizard-of-Oz approach and simulations of the pipeline process …

Learning fine-grained knowledge about contingent relations between everyday events
E Rahimtoroghi, E Hernandez, MA Walker – arXiv preprint arXiv …, 2017 – arxiv.org
… Elahe Rahimtoroghi, Ernesto Hernandez and Marilyn A Walker Natural Language and Dialogue Systems Lab Department of Computer Science, University … Our work is motivated by Penn Discourse Treebank (PDTB) definition of CONTINGENCY that has two types: CAUSE and …

Deep Memory Networks for Natural Conversations
??? – 2017 – s-space.snu.ac.kr
… Dataset ….. 54 5.3.2 Stanford Sentiment Treebank ….. 57 … 56 [Table 5.4] Test accuracies for sentiment analysis on the Stanford Sentiment Treebank ….. 58 …

Modelling semantic context of oov words in large vocabulary continuous speech recognition
I Sheikh, D Fohr, I Illina… – IEEE/ACM Transactions on …, 2017 – ieeexplore.ieee.org
Page 1. 598 IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 25, NO. 3, MARCH 2017 Modelling Semantic Context of OOV Words in Large Vocabulary Continuous Speech Recognition …

Annotation of semantic roles for the Turkish Proposition Bank
GG ?ahin, E Adal? – Language Resources and Evaluation – Springer
… analysed, POS tagged, and annotated with dependencies based on the grammar defined by its ancestor Metu Sabanc? Treebank (MST) (Oflazer et al … Unlike many other dependency treebanks, IMST provides links that enables nodes to have multiple heads as shown in Fig …

MojiTalk: Generating Emotional Responses at Scale
X Zhou, WY Wang – arXiv preprint arXiv:1711.04090, 2017 – arxiv.org
… emo- tion of the generated text. Li et al. (2016) use a reinforcement learning algorithm to improve the vanilla sequence-to-sequence model for non-task- oriented dialog systems, but their reinforced and Page 3. Figure 2: This is a …

Refining Word Embeddings Using Intensity Scores for Sentiment Analysis
LC Yu, J Wang, KR Lai, X Zhang – researchgate.net
… for evaluation, including SemEval-2013 Task 2: Sentiment analysis in Twitter [33] and the Stanford Sentiment Treebank (SST) [34 … method that injected both antonymy and synonymy relations into vector representations to improve the capability of dialog systems for distinguishing …

Theories and Approaches to the Study of Conversation and Interactive Discourse
WS Horton – The Routledge Handbook of Discourse Processes, 2017 – books.google.com
Page 44. p. 22 2 Theories and Approaches to the Study of Conversation and Interactive Discourse William S. Horton NORTHWESTERN UNIVERSITY Introduction Conversation is arguably the most fundamental means we have of interacting with others …

Improving scalability of inductive logic programming via pruning and best-effort optimisation
M Kazmi, P Schüller, Y Sayg?n – Expert Systems with Applications, 2017 – Elsevier
Skip to main content …

Synthesizing normalized faces from facial identity features
F Cole, D Belanger, D Krishnan, A Sarna… – IEEE Conference on …, 2017 – arxiv.org
… to a complete characterization of the maximum secret key rate achievable under a constraint on the total discussion rate. arXiv:1701.05011 [pdf, ps, other] Title: Assessing User Expertise in Spoken Dialog System Interactions …

Memory augmented neural networks with wormhole connections
C Gulcehre, S Chandar, Y Bengio – arXiv preprint arXiv:1701.08718, 2017 – arxiv.org
Page 1. Memory Augmented Neural Networks with Wormhole Connections Memory Augmented Neural Networks with Wormhole Connections Caglar Gulcehre gulcehrc@iro.umontreal.ca Montreal Institute for Learning Algorithms Universite de Montreal Montreal, Canada …

Negotiation of Antibiotic Treatment in Medical Consultations: A Corpus based Study
N Wang – Proceedings of ACL 2017, Student Research …, 2017 – aclweb.org
… practices. Current research for dialogue systems offer an alternative ap- proach … RID). In addition, the speech text was also word segmented corre- sponding to Chinese Penn Tree Bank segmenta- tion guideline (Xia et al., 2000) …

Charting a Way through the Trees
R Cooper – Theoretical Linguistics, 2017 – degruyter.com
… constructing the parser directly and not representing the grammar separately is like the most modern of computational approaches to parsing, where a parser for a language is learned from a corpus of material, although such systems are often trained on tree banks rather than …

Developing Semantic Role Labeler for Hindi and Urdu
MA Nomani – 2017 – web2py.iiit.ac.in
… in several NLP applications like machine translation, semantic role labeling, discourse analysis and dialogue systems. 2 … It involves building multi-layered and multi-representational Treebanks for Hindi and Urdu. The steps in the process of building the Urdu Treebank under this …

Nonrecurrent Neural Structure for Long-Term Dependence
S Zhang, C Liu, H Jiang, S Wei, L Dai… – IEEE/ACM Transactions …, 2017 – ieeexplore.ieee.org
Page 1. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 25, NO. 4, APRIL 2017 871 Nonrecurrent Neural Structure for Long-Term Dependence Shiliang Zhang, Cong Liu, Hui Jiang, Senior Member, IEEE, Si Wei, Lirong Dai, and Yu Hu …

EVALITA Goes Social: Tasks, Data
B Pierpaolo, N Malvina, S Rachele… – ITALIAN JOURNAL OF …, 2017 – iris.unito.it
Page 1. Volume 3, Number 1 june 2017 Emerging Topics at the Third Italian Conference on Computational Linguistics and EVALITA 2016 IJCoL Italian Journal Rivista Italiana of Computational Linguistics di Linguistica Computazionale ccademia university press aA Page …

Propositional Knowledge: Acquisition and Application to Syntactic and Semantic Parsing
B Cabaleiro Barciela – 2017 – e-spacio.uned.es
Page 1. Thesis for the Degree of Doctor of Philosophy 2017 Propositional Knowledge: Acquisition and Application to Syntactic and Semantic Parsing Bernardo Cabaleiro Barciela University Master’s Degree in Languages and Computer Systems (National Distance Education …

From Natural
I Pogrebezky – 2017 – idc.ac.il
Page 1. The Interdisciplinary Center, Herzliya Efi Arazi School of Computer Science M.Sc. program – Research Track From Natural Language descriptions to executable scenarios by Ilia Pogrebezky M.Sc. dissertation, submitted in partial fulfillment of the requirements …

LEARNING LOGIC RULES FROM TEXT USING STATISTICAL METHODS FOR NATURAL LANGUAGE PROCESSING
M KAZMI – 2017 – peterschueller.com
Page 1. LEARNING LOGIC RULES FROM TEXT USING STATISTICAL METHODS FOR NATURAL LANGUAGE PROCESSING by MISHAL KAZMI Submitted to the Graduate School of Engineering and Natural Sciences in Partial Fulfillment of the Requirements for the Degree of …

End-to-End Online Speech Recognition with Recurrent Neural Networks
K Hwang – 2017 – s-space.snu.ac.kr
… more important than the latency. On the other hand, the online ASR, or incremental speech recognition (ISR) [12], is more focused on the decoding latency, and usually employed for real-time applications such as spoken dialog systems or real-time auto- matic captioning …

Natural Language Processing for Social Media
A Farzindar, D Inkpen – Synthesis Lectures on Human …, 2017 – 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 …

Entity-Centric Discourse Analysis and Its Applications
X Wang – 2017 – repository.kulib.kyoto-u.ac.jp
Page 1. Title Entity-Centric Discourse Analysis and Its Applications( Dissertation_ ?? ) Author(s) Wang, Xun Citation Kyoto University (????) Issue Date 2017-11-24 URL https://dx.doi.org/10.14989/doctor.k20777 Right The …

Summarizing Dialogic Arguments from Social Media
A Misra, S Oraby, S Tandon, P Anand… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. arXiv:1711.00092v1 [cs.CL] 31 Oct 2017 Summarizing Dialogic Arguments from Social Media Amita Misra, Shereen Oraby, Shubhangi Tandon, Sharath TS, Pranav Anand and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High …

Modeling common sense knowledge via scripts
A Modi – 2017 – publikationen.sulb.uni-saarland.de
Page 1. Modeling Common Sense Knowledge via Scripts UNIVERSITÄT DES SAARLANDES Ashutosh Modi A dissertation submitted towards the degree Doctor of Engineering of the Faculty of Mathematics and Computer Science of Saarland University Saarbrücken, July 2017 …

Automatic Text Simplification
H Saggion – Synthesis Lectures on Human Language …, 2017 – 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 …

Handling long-term dependencies and rare words in low-resource language modelling
M Singh – 2017 – publikationen.sulb.uni-saarland.de
Page 1. Handling long-term dependencies and rare words in low-resource language modelling A dissertation submitted towards the degree of Doctor of Engneering of the Faculty of Mathematics and Computer Science of Saarland University by Mittul Singh, (M.Sc.) …

Computational models for semantic textual similarity
A González Aguirre – 2017 – addi.ehu.es
Page 1. UNIVERSITY OF THE BASQUE COUNTRY Computer Languages and Systems PhD Thesis Computational Models for Semantic Textual Similarity Aitor Gonzalez-Agirre 2017 (c)2017 AITOR GONZALEZ AGIRRE Page 2. Page 3 …

Multimodal Analysis of User-Generated Multimedia Content
R Shah, R Zimmermann – 2017 – Springer
… Examples of the second domain will include, but not limited to: computational and psychological models of emotions, bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning …

Generating variations in a virtual storyteller
SM Lukin – 2017 – search.proquest.com
… 20. 2.1.3 Overgenerate and Rank . . . . . 25. 2.2 Narrative and Dialogue Systems . . . . . 27. 2.2.1 Narrative Prose Generation … Previous research on NLG of linguistic style shows that dialogue systems are more. 22 …

Computational Linguistic Creativity: Poetry generation given visual input
M Loller-Andersen – 2017 – brage.bibsys.no
Page 1. Computational Linguistic Creativity: Poetry generation given visual input Malte Loller-Andersen Master of Science in Computer Science Supervisor: Björn Gambäck, IDI Department of Computer Science Submission date: June 2017 …

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