SVM (Support Vector Machine) & Dialog Systems 2015


Support Vector Machine

Resources:

  • dialog agent
  • natural language dialog system
  • natural language understanding module

See also:

100 Best Support Vector Machine VideosBest Dialog System Classifiers | SVM (Support Vector Machine) & Dialog Systems 2012 | SVM (Support Vector Machine) & Dialog Systems 2013 | SVM (Support Vector Machine) & Dialog Systems 2014


Using recurrent neural networks for slot filling in spoken language understanding G Mesnil, Y Dauphin, K Yao, Y Bengio… – … on Audio, Speech, …, 2015 – ieeexplore.ieee.org … speech recognition errors and poor modeling of natural language variability in expressing the same concept. For these reasons, spoken language understanding researchers employed statistical methods. These approaches … Cited by 50 Related articles All 16 versions

Matrix factorization with knowledge graph propagation for unsupervised spoken language understanding YN Chen, WY Wang, A Gershman… – Proceedings of ACL- …, 2015 – aclweb.org … Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, pages 483 … Spoken dialogue systems (SDS) typically require a predefined semantic ontology to train a spoken language understanding (SLU … Cited by 16 Related articles All 16 versions

Detecting Multiple Domains from User’s Utterance in Spoken Dialog System S Ryu, J Song, S Koo, S Kwon, GG Lee – … Language Dialog Systems and …, 2015 – Springer … Keywords Dialog system • Domain selection • Domain detection • Learning from positive and unlabeled examples • Hierarchical clustering • Support vector machine 10.1 Introduction Spoken dialog system (SDS) provides natural language interface between human and … Cited by 5 Related articles All 5 versions

HALEF: An Open-Source Standard-Compliant Telephony-Based Modular Spoken Dialog System: A Review and An Outlook D Suendermann-Oeft, V Ramanarayanan… – Natural Language …, 2015 – Springer … (eds.), Natural Language Dialog Systems and Intelligent … Classification tasks that leverage speech collected using a spoken dialog system are bound to certain constraints. … D. Suendermann-Oeft et al. We used support vector machine (SVM) classifiers to perform the classification … Cited by 6 Related articles All 21 versions

Contextual spoken language understanding using recurrent neural networks Y Shi, K Yao, H Chen, YC Pan… – … on Acoustics, Speech …, 2015 – ieeexplore.ieee.org … and slot filling [1]. SLU is a crit- ical component in spoken dialogue systems. … Network (RNN) has demon- strated outstanding performance in a variety of natural language pro- cessing … Due to its simplicity and robustness, Support Vector Machine with linear kernel (linear SVM) [2 … Cited by 10 Related articles All 7 versions

Bringing machine learning and compositional semantics together P Liang, C Potts – Annu. Rev. Linguist., 2015 – annualreviews.org … 2007, Turney & Pantel 2010). The two types of approaches share the long-term vision of achieving deep natural language understanding, but their day-to-day differences can make them seem unrelated and even incompatible. … Cited by 15 Related articles All 4 versions

SentiVoice-a system for querying hotel service reviews via phone TK Tran – … Technologies-Research, Innovation, and Vision for …, 2015 – ieeexplore.ieee.org … Pang B. et al. [16] use Naïve Bayes, Maximum Entropy and Support Vector Machine (SVM) to … [6] Fernando CN Pereira and Stuart M. Shieber, Prolog and Natural-Language Analysis. … [14] Nhut Pham, Quan Vu, “A Spoken Dialog System for Stock Information Inquiry,” in Proc. … Cited by 3 Related articles

Speech based emotion recognition V Sethu, J Epps, E Ambikairajah – Speech and Audio Processing for …, 2015 – Springer … in Proceedings of 2005 IEEE International Conference on Natural Language Processing and … acoustic features and linguistic information in a hybrid support vector machine-belief network … Towards real life applications in emotion recognition, in Affective Dialogue Systems, ed. by … Cited by 8 Related articles All 4 versions

Using hashtags to capture fine emotion categories from tweets SM Mohammad, S Kiritchenko – Computational Intelligence, 2015 – Wiley Online Library … They can be used in numerous applications of emotion detection, such as personality detection, automatic dialog systems, automatic tutoring systems … spelling mistakes, short forms, and various other properties that make such text difficult to process by natural language systems. … Cited by 46 Related articles All 8 versions

Efficient learning for spoken language understanding tasks with word embedding based pre-training Y Luan, S Watanabe, B Harsham – Sixteenth Annual Conference of the …, 2015 – Citeseer … as inputs to standard classification methods such as boosting, support vector machine, and logistic … Re- search and commercial spoken dialog systems,” in Proceedings of the 6th Annual … A. Deoras, “Application of deep belief networks for natural language understanding,” IEEE … Cited by 4 Related articles All 8 versions

A cognitive neural architecture able to learn and communicate through natural language B Golosio, A Cangelosi, O Gamotina, GL Masala – PloS one, 2015 – journals.plos.org … Natural language itself appears to be a strong symbolic activity, because words can be considered symbols used to … the field of NLP is dominated by machine learning approaches, which include neural-network based approaches, support vector machine, Bayesian approaches … Cited by 5 Related articles All 17 versions

Analysis of an extended interaction quality corpus S Ultes, MJP Sánchez, A Schmitt, W Minker – … Language Dialog Systems …, 2015 – Springer … Keywords Automatic dialoge systems evaluation • Statistical classification • Support vector machine • Hidden markov model … Assessing the performance of spoken dialogue systems (SDSs) is still an open issue, although … (eds.), Natural Language Dialog Systems and Intelligent … Cited by 2 Related articles All 6 versions

Combining heterogeneous deep neural networks with conditional random fields for Chinese dialogue act recognition Y Zhou, Q Hu, J Liu, Y Jia – Neurocomputing, 2015 – Elsevier … determine its pragmatic meaning. While in the dialogue system, speech act is evolved into DA. The DA tags … utterances are the same. DA recognition is very important for computers to understand natural-language dialogues. In the areas … Cited by 5 Related articles All 3 versions

Spoken language understanding in a nutrition dialogue system MB Korpusik – 2015 – dspace.mit.edu … 1.3.1 Previous Work To overcome the barrier preventing many obese individuals from easily tracking their food intake, we propose building a spoken dialogue system with which users simply … ranging from linguistics and natural language processing (NLP) to computer vision, … Cited by 3 Related articles All 3 versions

Quality-adaptive spoken dialogue initiative selection and implications on reward modelling S Ultes, M Kraus, A Schmitt, W Minker – … of the Special Interest Group on …, 2015 – aclweb.org … Walker ap- plied RL to a MDP-based dialogue system ELVIS for accessing emails over … 2008) or referring expres- sions (Janarthanam and Lemon, 2008) for natural language generation … Schmitt et al.(2011) estimated IQ with a Support Vector Machine using only automatically 2A … Cited by 3 Related articles All 10 versions

Discriminative methods for statistical spoken dialogue systems MS Henderson – 2015 – repository.cam.ac.uk … 121 Page 17. CHAPTER 1 INTRODUCTION Research on spoken dialogue systems seeks to create computer systems that can hold a conversation using natural language, just like a real human conversational partner. This is … Cited by 4 Related articles All 3 versions

Hierarchical emotion classification and emotion component analysis on Chinese micro-blog posts H Xu, W Yang, J Wang – Expert systems with applications, 2015 – Elsevier … related features and semantic orientation features from the posts and classify into 132 emotion classes using support vector machine (SVM … corpus are also reported, eg e-mails (Mohammad & Yang, 2011), novels (Mohammad, 2011) and Japanese dialog systems (Tokuhisa, Inui … Cited by 3 Related articles All 3 versions

One-Class Classification Model Based on Lexical Information and Syntactic Patterns H Lee, M Choi, H Kim – Journal of KIISE, 2015 – koreascience.or.kr … than a representative one-class classification model, one-class SVM(Support Vector Machine). … on Human Language Technology and Empirical Methods in Natural Language Processing, pp … Lee, “Detecting Multiple Domains from User’s Utterance in Spoken Dialog System,” Proc … Cited by 1 Related articles

Multi-Language Hypotheses Ranking And Domain Tracking for Open Domain Dialogue Systems PA Crook, JP Robichaud… – … Annual Conference of …, 2015 – research.microsoft.com … As natural language interaction, both spoken and typed, be- comes mainstream across a range … Figure 1: Schematic diagram of the experimental spoken dialog system where (a) is … using support vector machine (SVM) models [8]. These domain models use the system’s previous … Cited by 1 Related articles All 2 versions

Turn Segmentation into Utterances for Arabic Spontaneous Dialogues and Instance Messages ARA Elmadany, SM Abdou, M Gheith – arXiv preprint arXiv:1505.03081, 2015 – arxiv.org … Spoken Dialogue systems, Dialogues Language Understanding, Dialogue Utterances Segmentation, Dialogue Acts, Machine … Support Vector Machine (SVM) is a supervised machine learning that has been … International Journal on Natural Language Computing (IJNLC) Vol. … Cited by 1 Related articles All 6 versions

Automatic Speech Recognition-A Literature Survey on Indian languages and Ground Work for Isolated Kannada Digit Recognition using MFCC and ANN SB Harisha, S Amarappa, DSV Sathyanarayana – International Journal of … – eslibrary.org … of an intermediate matching kernel (IMK) for classification of sequential patterns using support vector machine (SVM) based … (2011) [79] developed a natural language Hindi speech … approach for gathering the linguistic resources needed to power a simple spoken dialog system. … Cited by 2 Related articles All 2 versions

Natural language processing in serious games: a state of the art D Picca, D Jaccard, G Eberlé – Int J Serious Games, 2015 – pdfs.semanticscholar.org … Objectives of using NLP NLP is used in order to allow a natural language conversation between the learner and an NPC. … vectors are then created using an n-gram approach, which are compared to the training set of features vector using a Support Vector Machine classifier. … Cited by 1 Related articles All 2 versions

Hypotheses Ranking and State Tracking for a Multi-Domain Dialog System Using Multiple ASR Alternates OZ Khan, JP Robichaud, P Crook… – … Conference of the …, 2015 – pdfs.semanticscholar.org … assistants typically involve the use of speech for natural language interaction to … in constructing a multi-domain dialog system that integrates heterogeneous spoken dialog systems. … is responsible for domain classification us- ing a binary support vector machine (SVM) classifier … Cited by 2 Related articles All 3 versions

A Study on Natural Expressive Speech: Automatic Memorable Spoken Quote Detection F Koto, S Sakti, G Neubig, T Toda, M Adriani… – Natural Language …, 2015 – Springer … (eds.), Natural Language Dialog Systems and Intelligent … Research related to spoken dialog systems has progressed from the traditional task-based frameworks to more sophisticated social agents (Dautenhahn 2007) that can engage … Support vector machine 64.80 66.71 68.08 … Cited by 1 Related articles All 8 versions

A Survey On Emotion Detection Techniques using Text in Blogposts R Hirat, N Mittal – International Bulletin of Mathematical Research, 2015 – academia.edu … Natural Language Processing (NLP) techniques have long been applied to automati- cally … centered communication systems are there such as dialogue systems, automatic answering … commendatory terms as features of classification, utilized Support Vector Machine classifier to … Cited by 1 Related articles

Automatic detection of miscommunication in spoken dialogue systems R Meena, JLG Skantze… – 16th Annual Meeting of …, 2015 – anthology.aclweb.org … extract- ed features from automatic speech recognizer (ASR), natural language understanding (NLU … A Support Vector Machine model was trained on automatically extractable features from ASR … table corpus, Krahmer et al., 2001) observed that dialogue system users provide … Cited by 2 Related articles All 15 versions

Automated identification of relative social status K Metcalf, D Leake – Proceedings of the Third Annual Conference on …, 2015 – Citeseer … The support vector machine was built using Scikit-Learn with a linear kernel and a c-value of one. … status is a feature that could be reliably identified and used by higher order social classification and dialogue systems. … Extracting social power relationships from natural language. … Cited by 1 Related articles All 7 versions

Twitter Sarcasm Detection Exploiting a Context-Based Model Z Wang, Z Wu, R Wang, Y Ren – International Conference on Web …, 2015 – Springer … Sarcasm detection Sentiment classification Support vector machine Sequential classification. 1 Introduction. Sentiment analysis in twitter has been one of the most popular research topics in NLP (Natural Language Processing) in the past decade, as shown in several recent … Cited by 3 Related articles

I-CARE: Intelligent Context Aware system for Recognizing Emotions from text Y Douiji, H Mousanif – 2015 10th International Conference on …, 2015 – ieeexplore.ieee.org … study of emotion classification of web blog corpora using support vector machine (SVM) and … on Human Language Technology and Empirical Methods in Natural Language Processing, 2005 … Using Context to Improve Emotion Detection in Spoken Dialog Systems,” in Interspeech … Cited by 1 Related articles

Human Affect Recognition: Audio?Based Methods B Schuller, F Weninger – Wiley Encyclopedia of Electrical and …, 2015 – Wiley Online Library … For practical purposes, such as in dialog systems, one can choose sentence or subsentence units of analysis in accordance with the segmentation chosen for the acoustic features X. … Interoperability of emotion recognizers with existing systems, such as dialog systems, is crucial. … Cited by 1 Related articles

A discriminative model for perceptually-grounded incremental reference resolution C Kennington, L Dia, D Schlangen – IWCS 2015, 2015 – aclweb.org … mapping between U and W was done with a support vector machine classifier. … Ideally for use downstream in a dialogue system, the reference resolver would make a … Situated Incremental Natural Language Under- standing using a Multimodal, Linguistically-driven Update Model … Cited by 2 Related articles All 11 versions

An Incremental Turn-Taking Model with Active System Barge-in for Spoken Dialog Systems T Zhao, AW Black, M Eskenazi – 16th Annual Meeting of the Special …, 2015 – aclweb.org … work is closely related to end-of-turn detection and incremental processing (IP) dialog systems. … The speaker consists of the Text-to-Speech (TTS) and Natural Language Gen- eration (NLG … the input state space into the action space: S? A?, using a Support Vector Machine (SVM … Cited by 1 Related articles All 9 versions

Comparing attribute classifiers for interactive language grounding Y Yu, A Eshghi, O Lemon – pdfs.semanticscholar.org … However, the George system only learns about 2 shapes and 8 colours. Our goal is to couple attribute classifiers with much wider coverage to the formal semantics of a full Natural Language dialogue system. 3 System Architecture … Cited by 2 Related articles All 7 versions

Towards Understanding Egyptian Arabic Dialogues ARA Elmadany, SM Abdou, M Gheith – arXiv preprint arXiv:1509.03208, 2015 – arxiv.org … his attends which called Dialogue Act (DA) classification, it is considered the key player for dialogue language understanding layer in automatic dialogue systems. … General Terms Natural Language Processing, Machine Learning, Support Vector Machine. … Related articles All 10 versions

Question Answering Dialogue System: A Brief Review L Sharma, V Dhir, K Kaur – ijcsit-apm.com … to extract information from the web or structured database based on the Dialogue system. … A. Query Processing The natural language query needs to be analysed and processed before … also be classified on the basis of algorithms such as Support Vector Machine [7], Template … Related articles

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 … evaluating the potential benefits of this approach to classifying human input to an ITS dialog system. … Exploring real-time student models based on natural-language tutoring sessions: A look at the rela … Support vector machine active learning with applications to text classification. … Related articles All 2 versions

User Information Extraction for Personalized Dialogue Systems T Hirano, N Kobayashi, R Higashinaka, T Makino… – SEMDIAL 2015 …, 2015 – flov.gu.se … They trained a classifier using a support vector machine (SVM). … In Proceedings of the 2015 International Workshop Series on Spo- ken Dialogue Systems Technology. … In Proceedings of 5th International Joint Conference on Natural Language Processing, pages 201–209. … Related articles All 5 versions

A multimodal adaptive dialogue manager for depressive and anxiety disorder screening: a Wizard-of-Oz experiment K Tsiakas, L Watts, C Lutterodt… – Proceedings of the 8th …, 2015 – dl.acm.org … an Adaptive Dialogue System able to have a conversation in natural language with PTSD … 68 feature statistics as explained above), we have adopted the Support Vector Machine regression technique … of 90 speech segments, recorded in the context of the dialog system has been … Related articles All 3 versions

Semi-supervised slot tagging in spoken language understanding using recurrent transductive support vector machines Y Shi, K Yao, H Chen, YC Pan… – 2015 IEEE Workshop on …, 2015 – ieeexplore.ieee.org … The RTSVM is a combination of a recurrent neural network (RNN) and a transductive support vector machine (TSVM), which uses a … Doddington, ‘The atis spoken language systems pilot corpus,” in The Proceedings ofthe DARPA Speech and Natural Language Workshop, 1990 … Related articles

A New Model for Question-Answer based Dialogue System for Indian Railways in Hindi Language L Sharma, V Dhir, K Kaur – Indian Journal of Science and Technology, 2015 – indjst.org … computer system is that which interacts with a human using natural language like English … A New Model for Question-Answer based Dialogue System for Indian Railways in Hindi … proposed a model using linear support vector machine that attains better results as compared to … Related articles

Improved multi-kernel SVM for multi-modal and imbalanced dialogue act classification Y Zhou, X Cui, Q Hu, Y Jia – 2015 International Joint …, 2015 – ieeexplore.ieee.org … So DA recognition is very important for computers to understand natural-language dialogues and … also essential to determine the DA tags in a Chinese dialogue system [5]. While … and has potential advantages in dealing with imbalanced data as support vector machine (SVM) [13 … Related articles

Possibilities, Challenges and the State of the Art of Automatic Speech Recognition in Air Traffic Control VN Nguyen, H Holone – World Academy of Science, Engineering and …, 2015 – waset.org … Hybrid support vector machine/hidden markov model approach for continuous speech recognition. … In Proceedings of the International Conference on Natural Language Processing (ICON–2005), page 79. … Parole: a vocal dialogue system for air traffic control training. … Cited by 1 Related articles All 2 versions

A comparative study of evolving fuzzy grammar and machine learning techniques for text categorization NM Sharef, T Martin, KA Kasmiran, A Mustapha… – Soft Computing, 2015 – Springer … It has been utilized in many applications, such as dialogue systems, named entity recognition … The Natural Language Processing (NLP) community deals with this issue by identifying the constituents … 2012 ), support vector machine (Joachims 1998 ), and decision rules (Apté et al. … Related articles All 3 versions

An Ensemble-Based Classification Approach to Model Human-Machine Dialogs D Griol, AS de Miguel – Conference of the Spanish Association for Artificial …, 2015 – Springer … Recognition (ASR), Spoken Language Understanding (SLU), Dialog Management (DM), Natural Language Generation (NLG … n-gram based classifier, a decision tree classifier, a support vector machine classifier, a … its interaction with the rest of the modules in the dialog system. … Related articles

Emotion recognition based on EEG changes in movie viewing S Liu, J Meng, D Zhang, J Yang, X Zhao… – 2015 7th …, 2015 – ieeexplore.ieee.org … A support vector machine (SVM) was performed finally. … using bio-sensors: First steps towards an automatic system,” in Affective dialogue systems, ed: Springer … of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, 2005, pp … Related articles

Sarcasm Detection in Social Media A Signhaniya, G Shenoy, R Kondekar – rohitkondekar.github.io … report presents a machine learning approach combined with Natural Language techniques, thereby … in building better sentiment analyzers for review summarization, dialogue systems and review … They used two classifiers – support vector machine (SVM) with sequential minimal … Related articles

Statistical Response Method and Learning Data Acquisition using Gamified Crowdsourcing for a Non-task-oriented Dialogue Agent Y Enokibori, K Takahashi, K Mase – … 2014, Angers, France, March 6-8, …, 2015 – Springer … For comparison, we used a classification method, support vector machine (SVM). … Carroll, J., Nickerson, JS: Evaluating automatic dialogue strategy adaptation for a spoken dialogue system. … J.: ELIZA-a computer program for the study of natural language communication between … Related articles All 2 versions

A Speech-Based Approach to Video Retrieval B QasemiZadeh, J Shen, IM O’Neill, P Hanna… – pars.ie … based retrieval of the video content in the context of a broader spoken dialogue system . … eg information seeking, in addition to a first order logic representation of natural language utterances … system, the first 50 components are input to a trained Support Vector Machine (SVM) as … Related articles

Speech emotion recognition using SVM with thresholding fusion S Gupta, A Mehra – Signal Processing and Integrated …, 2015 – ieeexplore.ieee.org … MLBC) and K- nearest Neighbors approach (KNN) [4], support vector machine (SVM), Naive … for human like interaction with machines through natural language processing and … types of communication system such as automatic answering system, dialogue system and human … Related articles

Prediction of relevant biomedical documents: a human microbiome case study P Thompson, JC Madan… – BioData …, 2015 – biodatamining.biomedcentral.com … Medical Literature Analsyis and Retrieval System (MEDLARS) [23] and Saracevic’s own evaluations of the DIALOG system [24–26]. … results, we suspect that significantly better results will require an approach based on natural language understanding. … Support Vector Machine. … Related articles All 13 versions

Discourse Relation Recognition by Comparing Various Units of Sentence Expression with Recursive Neural Network A Otsuka, T Hirano, C Miyazaki, R Masumura… – 2015 – aclweb.org … coherence of sentences, it has potential applications in many natural language processing (NLP … is identified by a discriminative classifier such as a support vector machine (SVM … selec- tion using intermediate expression vectors and to consider applications for dialogue systems. … Related articles All 8 versions

A Multimodal Sentiment Analysis Scheme to Detect Hidden Sentiments VD Bhat, VS Deshpande, R Sugandhi – spvryan.org … Though Sentiment Analysis is mainly considered as a sub branch of Natural Language Processing, SA is also … Pang et. al. [7] has compared three standard text classification algorithms – Naïve Bayes (NB), Maximum Entropy (ME) and Support Vector Machine (SVM) in their … Related articles

Supervised Hierarchical Classification for Student Answer Scoring I Aldabe, OL de Lacalle, I Lopez-Gazpio… – arXiv preprint arXiv: …, 2015 – arxiv.org … One of the aims of educational natural language pro- cessing is to provide useful feedback … and annotated during the evaluation of the BEETLE II tutorial dialogue system (Dzikovska et … the hierarchical structure is defined, a bi- nary multi-class Support Vector Machine hierar- chy … Related articles All 4 versions

Non-speaker information reduction from Cosine Similarity Scoring in i-vector based speaker verification H Zeinali, A Mirian, H Sameti, B BabaAli – Computers & Electrical …, 2015 – Elsevier … 2. WCCN: The principal goal of this method is to minimize the false rejection and false acceptance errors in the training stage of Support Vector Machine (SVM). In other words, this method scales the space to remove the dimensions with high intra-class variance. … Related articles All 3 versions

Speech Recognition in Indian Languages—A Survey M Sarma, KK Sarma – Recent Trends in Intelligent and Emerging Systems, 2015 – Springer … can be consumed by the common public and to enable natural language transactions between … where a spoken dialogue system is designed to use in agricultural commodities task … Support vector machine (SVM) classifier is used as the classifier and broadcast news corpus of … Related articles All 5 versions

Extracting Sentiment from Healthcare Survey Data D Georgiou, A MacFarlane, T Russell-Rose – researchgate.net … analysis and healthcare. II. SENTIMENT ANALYSIS Sentiment Analysis (SA) is concerned with the investigation of opinions, thoughts and feelings. It is used as a tool to understand Natural Language Processing (NLP). It aims to … Related articles

Weakly Supervised Natural Language Processing Framework for Abstractive Multi-Document Summarization: Weakly Supervised Abstractive Multi-Document … P Li, W Cai, H Huang – Proceedings of the 24th ACM International on …, 2015 – dl.acm.org … Categories and Subject Descriptors I.2.7 [Natural Language Processing]: Text analysis … Because the number of labeled data is very small, the supervised learning models and many semi-supervised learning (eg trans- ductive support vector machine) methods cannot get good … Related articles

Extracting sentiment from healthcare survey data: An evaluation of sentiment analysis tools D Georgiou, A MacFarlane… – … Conference (SAI), 2015, 2015 – ieeexplore.ieee.org … analysis and healthcare. II. SENTIMENT ANALYSIS Sentiment Analysis (SA) is concerned with the investigation of opinions, thoughts and feelings. It is used as a tool to understand Natural Language Processing (NLP). It aims to … Related articles

Incrementally Tracking Reference in Human/Human Dialogue Using Linguistic and Extra-Linguistic Information N UCRI – zzz.cl.cs.titech.ac.jp … an incremental one by applying that model at each word (Khouzaimi et al., 2014), but we would argue that more modeling effort is required in order for the model to work in an interactive dialogue system, see (Schlangen … (2011) applied a support vector machine-based ranking … Related articles All 9 versions

A proposal for the development of adaptive spoken interfaces to access the Web D Griol, JM Molina, Z Callejas – Neurocomputing, 2015 – Elsevier … of an appropriate dialog management strategy is at the core of dialog system engineering. … classifier, an n-gram based classifier, a decision tree classifier, a support vector machine classifier, a … also proven to be useful in for other tasks related to natural language processing [83 … Cited by 1 Related articles All 3 versions

Content Finder Assistant R Laroche – Intelligence in Next Generation Networks (ICIN), …, 2015 – ieeexplore.ieee.org … Since we are limited by the capability to automatically generate a well-formed natural language question, the … M. Geist, F. Lefevre, and O. Pietquin, “User sim- ulation in dialogue systems using inverse … [4] C. Cortes and V. Vapnik, “Support vector machine,” Machine learning, vol. … Related articles

Unsupervised Learning and Modeling of Knowledge and Intent for Spoken Dialogue Systems YN Chen – target, 2015 – cs.cmu.edu … that studies the problems intrinsic to the processing and manipulation of natural language. … Spoken Language Understanding is a component of a spoken dialogue system, which parses … SVM Support Vector Machine is a supervised learning method used for classification and … Related articles All 10 versions

Investigating student interactions with tutorial dialogues in EER-Tutor M Elmadani, A Mitrovic… – … and Practice in …, 2015 – telrp.springeropen.com … The Geometry Explanation Tutor allows students to give natural language explanations about their problem-solving steps. … A support vector machine-based classification was used to predict problem-solving cognition states such as planning as well as a user’s performance. … Related articles All 3 versions

Question Processing for Arabic Question Answering System HM Al Chalabi – 2015 – bspace.buid.ac.ae … research community of the Artificial Intelligence. Since 1960s, when the field was at beginning, a set of database related to the natural language have been created like; dialog systems, language understanding systems, and front-ends. Simmons (1965) illustrates at … Related articles

Backchannel prediction for Mandarin human-computer interaction MAO Xia, P Yiping, XUE Yuli, LUO Na… – … on Information and …, 2015 – search.ieice.org … key words: human-computer interaction, virtual agent, backchannel, Man- darin, support vector machine 1. Introduction … Nishimura et al. developed a Japanese spoken dialog system which could spontaneously generate chat-like responses including backchannel[12]. … Related articles All 5 versions

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 4 Related articles All 5 versions

Social talk capabilities for dialogue systems T Klüwer – 2015 – universaar.uni-saarland.de … Page 17. 16 SOCIAL-TALK CAPABILITIES FOR DIALOGUE SYSTEMS website. Task-oriented dialogue systems are a lot easier to develop than non-task-oriented systems, since unrestricted natural language input is impossible to process by machines. … Cited by 1 Related articles All 3 versions

Code-switching event detection by using a latent language space model and the delta-Bayesian information criterion CH Wu, HP Shen, CS Hsu – IEEE/ACM Transactions on Audio, …, 2015 – ieeexplore.ieee.org … switching event detection is becoming indispensable in human–machine communication applications, particularly in multilingual spoken dialog systems. … event modeling, approaches based on the Gaussian mixture model (GMM) [8]– [10], support vector machine (SVM) [11]–[13 … Related articles All 5 versions

Situated Learning and Understanding of Natural Language Y Artzi – 2015 – digital.lib.washington.edu … cable. Logical forms can represent questions in natural language interfaces to databases, where the execution will be a database query. In dialog systems, logic can represent the meaning of user requests, which are then evaluated to plan the system response. … Related articles All 4 versions

Emotional Agents–State of the Art and Applications M Ivanovi?, Z Budimac, M Radovanovi?… – Computer Science and …, 2015 – 147.91.177.25 … For example, a support vector machine can be used to classify motion signatures as either non-expressive, or belonging to one of the predefined six categories [13]. … The use of natural language processing techniques to perform automated categorization of news stories on the … Related articles All 4 versions

Data-driven deep-syntactic dependency parsing M BALLESTEROS, B BOHNET… – Natural Language …, 2015 – Cambridge Univ Press Page 1. Natural Language Engineering: page 1 of 36. c Cambridge University Press 2015 doi:10.1017/S1351324915000285 1 Data-driven deep-syntactic dependency parsing† MIGUEL BALLESTEROS1, BERND BOHNET2 … Cited by 2 Related articles All 3 versions

[BOOK] Advanced Applications of Natural Language Processing for Performing Information Extraction MJF Rodrigues, AJ da Silva Teixeira – 2015 – Springer … the topics covered in this series include the presentation of real life com- mercial deployment of spoken dialog systems, contemporary methods … and CEO of Linguistic Technology Systems, a NJ-based think tank for intelligent design of advanced natural language based emotion … Related articles All 4 versions

Structural information aware deep semi-supervised recurrent neural network for sentiment analysis W Rong, B Peng, Y Ouyang, C Li, Z Xiong – Frontiers of Computer Science, 2015 – Springer … Embedding words into a continuous vector space has a long history in the domain of natural language processing. … Another popular method is TSVM [52], which is a support vector machine (SVM) based model benefiting from both la- belled and unlabelled data and minimizes … Cited by 2 Related articles All 4 versions

Regional Information Video Searches Using Word Searches Generated by Twitter Posts M Takeda, N Kobayashi, F Kitagawa… – … Informatics (IIAI-AAI), …, 2015 – ieeexplore.ieee.org … In addition, as a means for removing unnecessary posts, the support vector machine(SVM) machine[13 … for NICT Kyoto tour dialogue corpus to construct statistical dialogue systems”, Proc. … Linguistics and the 4th International Joint Conference on Natural Language Processing, pp … Related articles All 2 versions

A generalized framework for medical image classification and recognition M Abedini, NCF Codella, JH Connell… – IBM Journal of …, 2015 – ieeexplore.ieee.org … Ebadollahi et al. [11] proposed a chamber detector based on a generic cardiac chamber template. They used a Markov Random Field (MRF) to locate the chambers and a multi-class Support Vector Machine (SVM) classifier to predict the chamber view. … Cited by 6 Related articles All 4 versions

Semantic mapping for mobile robotics tasks: A survey I Kostavelis, A Gasteratos – Robotics and Autonomous Systems, 2015 – Elsevier … aiming to augment the navigation capabilities and the task-planning, as well as to bridge the gap in human–robot interaction (HRI), see eg [2], [3] and [4]. Especially the work in [4] addresses semantic mapping with emphasis on HRI by using natural language, thus enabling the … Cited by 19 Related articles All 5 versions

Evaluation of the Industrial and Social Impacts of Academic Research Using Patents and News S Iinumaa, S Fukudaa, H Nanbaa, T Takezawaa – ls.info.hiroshima-cu.ac.jp … They employed the support vector machine approach, which obtained higher precision than the conditional random field [15] approach. … title>Yahoo Acquires SkyPhrase Yahoo has acquired SkyPhrase, a startup that builds natural language processing technology … Related articles

SENSEI Coordinator M Kabadjov, EA Stepanov, F Celli, SA Chowdhury… – sensei-conversation.eu … Question Answering corpus/lexicon NE Named Entity NLP Natural Language Processing NN … conversa- tion summarization (both spoken and written), dialogue systems, etc.; and … we used Sequential Minimal Optimisation (SMO), a support vector machine implementation with its … Related articles

Fuzzy Logic in Speech Technology-Introductory and Overviewing Glimpses HN Teodorescu – Fifty Years of Fuzzy Logic and its Applications, 2015 – Springer … These pronunciation-related statistics are then combined with the so called natural language (NL) language models, which include the … qualities on a tense to breathy dimension”, these authors introduce a fuzzy-input fuzzy-output support vector machine (F2SVM) algorithm that … Related articles All 2 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 … a Natural Language Processing Lab, Department of … 2. Related work. Research on spoken dialogue systems has been progressing for at least forty years, and many systems exist, from prototypes to commercial strength (please see Tur and De Mori, 2011 for a recent overview). … Cited by 3 Related articles All 9 versions

Non-Sentential Utterances in Dialogue: Experiments in classification and interpretation P Dragone – arXiv preprint arXiv:1511.06995, 2015 – arxiv.org … 64 4.5.1 Dialogue system architecture . . . . . … NLG Natural Language Generation NLU Natural Language Understanding NSU Non-Sentential Utterance … SMO Sequential Minimal Optimization SVM Support Vector Machine TSVM Transductive Support Vector Machine … Cited by 1 Related articles All 12 versions

Corpus Annotation and Usable Linguistic Features AC Fang, J Cao – Text Genres and Registers: The Computation of …, 2015 – Springer … of different types. Man–machine dialogue systems, as an example, perform at a high level of linguistic sophistication that draws from annotations on the basis of lexis, grammar, semantics and speech processing. Having said …

Automated Quality Assurance of Non-Functional Requirements for Testability A Rashwan – 2015 – spectrum.library.concordia.ca … ML Machine Learning NFR Non-Functional Requirement NLP Natural Language Processing NN Neural Network … SRS Software Requirement Specification SVM Support Vector Machine TF-IDF Term Frequency – Inverse Document Frequency UML Unified Modeling Language … Related articles All 3 versions

Exploring the Benefits of Context in 3D Gesture Recognition for Game-Based Virtual Environments EM Taranta II, TK Simons, R Sukthankar… – ACM Transactions on …, 2015 – dl.acm.org … and is based on Rubine’s popular linear discriminator [Rubine 1991]; CA-DTW, a contextually opti- mized GPU implementation of dynamic time warping (DTW) that utilizes context to reduce computational overhead; and CA-SVM, a multiclass support vector machine extended to … Cited by 2 Related articles All 2 versions

A system for recognizing human emotions based on speech analysis and facial feature extraction: applications to Human-Robot Interaction M Rabiei – 2015 – dspace-uniud.cineca.it … Some works tried to incorporate spoken dialogue system technology and service robots. … solved the speaker independent speech recognition with new Support Vector Machine (SVM) model … several researches on emotion classification system in the field of Natural Language … Related articles All 2 versions

Automatic irony-and sarcasm detection in Social media E Forslid, N Wikén – 2015 – diva-portal.org … An accuracy of 87% was obtained on the Amazon data with the Support Vector Machine. … 10 Page 15. 4 Theory / Text Categorization Text categorization is an area that overlaps both with Natural Language Processing (NLP) and Machine learning. … Related articles

Sarcasm Detection in Twitter: “All Your Products Are Incredibly Amazing!!!”-Are They Really? M Bouazizi, T Ohtsuki – 2015 IEEE Global Communications …, 2015 – ieeexplore.ieee.org … of features including the use of profanity, slangs and “semantic validity”; and used Support Vector Machine (SVM) to … Tepperman, D. Traum, and SS Narayanan, “Yeah right: Sarcasm recognition for spoken dialogue systems,” in Proc … Computational Natural Language Learning, pp … Related articles

Multiple topic identification in human/human conversations X Bost, G Senay, M El-Bèze, R De Mori – Computer Speech & Language, 2015 – Elsevier … Hidden topic features obtained with lda have been combined with other features in support vector machine (svm) classifiers to assign spoken documents to relevance classes (Wintrode, 2011) using asr word lattice hypotheses. … Cited by 1 Related articles All 3 versions

Content-based Tweets Semantic Clustering and Propagation MA Michalakos – 2015 – repository.ihu.edu.gr … Hyun Woo Kim (2010) in his thesis, analyses the use of four supervised learning algorithms as gender classifiers. Support Vector Machine, Naïve Bayes, … 2.3 Automatic Topic Labeling Despite that natural language processing is used frequently to perform sentiment analysis it … Related articles

[BOOK] Biometric and intelligent decision making support A Kaklauskas – 2015 – Springer … Therefore this book deliberates the intelligent databases, hardware (sen- sors, iris camera hardware, hardware for fingerprint biometric identification, etc.), and computer human interfaces (gesture, intelligent user, motion tracking, voice and natural-language interfaces) in … Cited by 5 Related articles All 4 versions

A Survey on perceived speaker traits: Personality, likability, pathology, and the first challenge B Schuller, S Steidl, A Batliner, E Nöth… – Computer Speech & …, 2015 – Elsevier The INTERSPEECH 2012 Speaker Trait Challenge aimed at a unified test-bed for perceived speaker traits – the first challenge of this kind: personality in the f. Cited by 10 Related articles All 14 versions

[BOOK] NLTK essentials N Hardeniya – 2015 – books.google.com … Table of Contents Preface v Chapter 1: Introduction to Natural Language Processing 1 Why learn NLP? … space model 66 The probabilistic model 67 Speech recognition 68 Text classification 68 Information extraction 70 Question answering systems 70 Dialog systems 71 Word … All 6 versions

[BOOK] Language Identification Using Excitation Source Features KS Rao, D Nandi – 2015 – Springer … the topics covered in this series include the presentation of real life commercial deployment of spoken dialog systems, contemporary methods … and CEO of Linguistic Technology Systems, a NJ-based think tank for intelligent design of advanced natural language based emotion … Related articles All 6 versions

Novel methods for text preprocessing and classification T Gasanova – 2015 – oparu.uni-ulm.de … 3.1 Overview of Spoken Dialogue Systems . … Gasanova, E. Semenkin and W. Minker, “Text Categorization Methods Application for Natural Language Call Routing … Gasanova and W. Minker, “Co-operation of biology related algorithms for support vector machine automated design … Related articles All 3 versions

[BOOK] Sentic computing: a common-sense-based framework for concept-level sentiment analysis E Cambria, A Hussain – 2015 – books.google.com … bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning etc.). … that will help change the way we approach sentiment, emotion, and affect in natural language processing and … Cited by 43 Related articles All 2 versions

Robot task planning and explanation in open and uncertain worlds M Hanheide, M Göbelbecker, GS Horn, A Pronobis… – Artificial Intelligence, 2015 – Elsevier A long-standing goal of AI is to enable robots to plan in the face of uncertain and incomplete information, and to handle task failure intelligently. This paper. Cited by 13 Related articles All 3 versions

[BOOK] Advances in Artificial Intelligence and Its Applications: 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Cuernavaca, Morelos, … OP Lagunas, OH Alcántara, GA Figueroa – 2015 – books.google.com … The first volume, Advances in Artificial Intelligence and Soft Computing, contains 46 papers structured into eight sections: – Invited Paper – Natural Language Processing – Logic and Multi-agent Systems – Bioinspired Algorithms – Neural Networks – Evolutionary Algorithms … Related articles

The Self-taught Speech Interface B Ons – 2015 – lirias.kuleuven.be … grammar. Hence, users have to adapt to the constraints of the vocal interface. Currently, natural language interfaces are integrated in voice enabled applications such as the voice controlled digital assistant in smartphones. These … Related articles

Sentic Computing E Cambria, A Hussain – Cognitive Computation, 2015 – Springer … bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning etc.). … that will help change the way we approach sentiment, emotion, and affect in natural language processing and … Cited by 2 Related articles All 8 versions

[BOOK] Computational Linguistics and Intelligent Text Processing: 16th International Conference, CICLing 2015, Cairo, Egypt, April 14-20, 2015, Proceedings A Gelbukh – 2015 – books.google.com … 321 Diana Inkpen, Ji Liu, Atefeh Farzindar, Farzaneh Kazemi, and Diman Ghazi Natural Language Generation and Text Summarization Satisfying Poetry Properties Using … 348 Rivindu Perera and Parma Nand A Dialogue System for Telugu, a Resource-Poor Language….. … Related articles All 2 versions

[BOOK] Text Genres and Registers: The Computation of Linguistic Features CA Fang, J Cao – 2015 – books.google.com … His research interests include corpus linguistics, computational linguistics, dialogue systems and information retrieval. … It has as a result revolutionised natural language processing systems that can now robustly handle unforeseen phenomena in language through the … Related articles

Automatic Detection of Verbal Deception E Fitzpatrick, J Bachenko… – Synthesis Lectures on …, 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 1 Related articles All 4 versions

Spoken content retrieval—beyond cascading speech recognition with text retrieval L Lee, J Glass, H Lee, C Chan – IEEE/ACM Transactions on …, 2015 – ieeexplore.ieee.org Page 1. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 23, NO. 9, SEPTEMBER 2015 1389 Spoken Content Retrieval—Beyond Cascading Speech Recognition with Text Retrieval … Cited by 4 Related articles All 6 versions

Question Generation from Knowledge Graphs D Seyler, K Berberich, G Weikum – 2015 – pubman.mpdl.mpg.de … Abstract In this thesis we present a novel approach for generating natural language questions, using factual information from a knowledge graph and automatically assessing their difficulty. … The resulting output is a question in natural language, that abides the input criteria. … Related articles