WEKA & Dialog Systems 2015


Resources:

  • halef .. open source vxml-based spoken dialog system
  • weka .. collection of machine learning algorithms for data mining

Wikipedia:

See also:

WEKA & Dialog Systems 2014


HALEF: An Open-Source Standard-Compliant Telephony-Based Modular Spoken Dialog System: A Review and An Outlook D Suendermann-Oeft, V Ramanarayanan… – … Dialog Systems and …, 2015 – Springer … 1994) Weka: a machine learning workbench. In: Proceedings of the 1994 second Australian and New Zealand conference on intelligent information systems. IEEE, Brisbane, pp 357–361 Jurcícek F, Dušek O, Plátek O, Žilka L (2014) Alex: a statistical dialogue systems framework … Cited by 9 Related articles All 22 versions

A tutorial dialogue system for real-time evaluation of unsupervised dialogue act classifiers: Exploring system outcomes A Ezen-Can, KE Boyer – … Conference on Artificial Intelligence in Education, 2015 – Springer … Fig. 2 presents the architecture diagram of the dialogue system. 2.2 Dialogue Act Classification … Supervised Dialogue Act Classification. For supervised dialogue act classification, we use an off-the-shelf decision tree classifier from Weka [11] and train it on dialogue act tags [20]. … Cited by 5 Related articles All 4 versions

User adaptive restoration for incorrectly segmented utterances in spoken dialogue systems K Komatani, N Hotta, S Sato… – 16th Annual Meeting of …, 2015 – anthology.aclweb.org … 2009. The WEKA data mining software: an update. SIGKDD Explor. … 2005. Re- sponse timing detection using prosodic and linguistic information for human-friendly spoken dialog systems. Journal of The Japanese Society for Artificial Intellignece, 20 (3): 220–228. … Cited by 3 Related articles All 10 versions

Automatic detection of miscommunication in spoken dialogue systems R Meena, JLG Skantze… – 16th Annual Meeting of …, 2015 – anthology.aclweb.org … Integrating multi- ple knowledge sources for utterance-level confi- dence annotation in the CMU Communicator spo- ken dialog system. Technical Report CS-190, Car- negie Mellon University, Pittsburgh, PA. Cohen, W.(1995). … The WEKA Data Mining Software: An Update. … Cited by 3 Related articles All 15 versions

An analysis towards dialogue-based deception detection Y Tsunomori, G Neubig, S Sakti, T Toda… – … Dialog Systems and …, 2015 – Springer … in speech across languages and cultures and also to provide further resources for our work on deception detecting dialogue systems, which will use … To solve this classification, we use Bagging of decision trees (Breiman 1996) as implemented in the Weka toolkit, which gave the … Cited by 3 Related articles All 7 versions

Using Summarization to Discover Argument Facets in Online Idealogical Dialog. A Misra, P Anand, JEF Tree, MA Walker – HLT-NAACL, 2015 – anthology.aclweb.org … Amita Misra, Pranav Anand, Jean Fox Tree, and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High … regression problem and evaluate support vector regression and linear regres- sion for 10-fold cross validation using the Weka ma- chine … Cited by 11 Related articles All 7 versions

Detecting repetitions in spoken dialogue systems using phonetic distances. J Lopes, G Salvi, G Skantze, A Abad, J Gustafson… – INTERSPEECH, 2015 – inesc-id.pt … is the clue: breakdown in human-machine interaction,” in Proceedings of the ISCA Tuto- rial and Research Workshop Error Handling in Spoken Dialogue Systems, Chteau d … [16] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and IH Witten, “The WEKA data mining … Cited by 1 Related articles All 7 versions

Evaluation of a fully automatic cooperative persuasive dialogue system T Hiraoka, G Neubig, S Sakti, T Toda… – … Dialog Systems and …, 2015 – Springer … Persuasive Dialogue System … Abstract In this paper, we construct and evaluate a fully automated text-based cooperative persuasive dialogue system, which is able to persuade the user to take a specific action while maintaining user satisfaction. … Cited by 1 Related articles All 7 versions

Towards a hybrid NLG system for Data2Text in Portuguese JC Pereira, A Teixeira, JS Pinto – Information Systems and …, 2015 – ieeexplore.ieee.org … BAGEL – was presented in [7]. It is designed to produce natural utterances within a large dialogue system domain. Another purpose is minimizing the development effort. … We used libSVM implementation, running under Weka [17], with the default configuration. … Cited by 2 Related articles All 5 versions

Social talk capabilities for dialogue systems T Klüwer – 2015 – universaar.uni-saarland.de … Social Talk Capabilities for Dialogue Systems Tina Klüwer T in a K lü w e r S o cia l Ta lk C a p a b ilitie … Page 2. Tina Klüwer Social Talk Capabilities for Dialogue Systems universaar Universitätsverlag des Saarlandes Saarland University Press Presses Universitaires de la Sarre … Cited by 1 Related articles All 4 versions

Multicriteria neural network design in the speech-based emotion recognition problem C Brester, E Semenkin, M Sidorov… – Informatics in Control, …, 2015 – ieeexplore.ieee.org … However, in this paper we consider the human emotion recognition problem in the framework of intellectual spoken dialogue systems and, therefore, we apply only … Firstly, the conventional MLP classifier implemented in the program system WEKA (Hall et al., 2009) was applied. … Cited by 1 Related articles All 4 versions

Dialogue Act Recognition for Text-based Sinhala S Palihakkara, D Sahabandu, A Shamsudeen… – Proceedings of the 12th … – ltrc.iiit.ac.in … 2009. The WEKA data mining software: an update. … Machine learning for shallow interpretation of user utterances in spoken dialogue systems. In Proceedings of the EACL-03 Workshop on Dialogue Systems: Interaction, Adaptation and Styles of Management, pages 69– 78. … Cited by 1 Related articles

Recognition of Paralinguistic Information in Spoken Dialogue Systems for Elderly People H Pérez-Espinosa, J Martínez-Miranda – Mexican International Conference …, 2015 – Springer … It contains recordings of children, non-natives and elderly people interacting in Dutch with a spoken dialogue system. … We applied the machine-learning algorithm Support Vector Machines, as implemented in WEKA [13], for building a classifier. … Related articles

Example-based dialog modeling for a mobile system W Franco, TCJPP Gomes, R Castro, RMC Andrade… – researchgate.net … With the set of DAs set, we do not need to search for the sentence in the entire database which consequently improve the performance and accuracy of the dialogue system. … In the first moment, the Weka tool was used with the extracted features to generate classification models. … Related articles

Audio Features for the Classification of Engagement C Elias, JP Cabral, N Campbell – tara.tcd.ie … can be applied to improve the quality of interactions in dialogue systems or to help to make human intervention decisions in automated dialogue systems such as in call … A random forest learning algorithm implemented in Weka [11] was used for the classification of engagement. … Related articles

Opportunities and obligations to take turns in collaborative multi-party human-robot interaction M Johansson, G Skantze – Proc. SIGDIAL, 2015 – aclweb.org … The logged utterances from the dialogue system were then added as a third track of IPUs. … Page 330. in the WEKA toolkit (Hall et al., 2009), using the default parameters. All results in this section are based on 10-fold cross-validation. … Cited by 6 Related articles All 15 versions

ZOE: A cloud-less dialog-enabled continuous sensing wearable exploiting heterogeneous computation ND Lane, P Georgiev, C Mascolo, Y Gao – Proceedings of the 13th …, 2015 – dl.acm.org … personal, so- cial and place information) on continuously sensed data; while also offering this data not only within conventional analytics but also through a speech dialog system that is able to answer impromptu casual questions from users. … Cited by 6 Related articles All 10 versions

Do Human-Agent Conversations Resemble Human-Human Conversations? D Griol, JM Molina – Distributed Computing and Artificial Intelligence, 12th …, 2015 – Springer … The C4.5 decision tree learning algorithm has been used for the learning of these models, using the Weka machine learning software for classifying the complete list of features contained in the history register. … 3 Case Application: The Facilisimo Spoken Dialog System … Related articles All 3 versions

Towards Emotionally Sensitive Conversational Interfaces for E-therapy D Griol, JM Molina, Z Callejas – … Work-Conference on the Interplay Between …, 2015 – Springer … This is the case of most spoken dialog systems, in which a baseline algorithm which always chooses “neutral” would have a very high accuracy … algorithm, a genetic search, and a ranking filter using the default values of their respective parameters provided by the Weka toolkit. … Related articles

Modeling users emotional state for an enhanced human-machine interaction D Griol, JM Molina – … Conference on Hybrid Artificial Intelligence Systems, 2015 – Springer … This is the case of most information providing spoken dialog systems, in which a baseline algorithm which always chooses “neutral” would have a very … algorithm, a genetic search, and a ranking filter using the default values of their respective parameters provided by Weka [21]. … Cited by 2 Related articles

Fundamentals of adaptive intelligent tutoring systems for self-regulated learning RA Sottilare – 2015 – DTIC Document … If you are interested in other machine learning techniques, check out WEKA, an open-source software tool for machine learning: http://www.cs.waikato.ac.nz/ml/weka/. 5.2 Instructional Management in Support of Self-Regulated Learning … Cited by 2 Related articles All 5 versions

Identifying various kinds of event mentions in k-parser output A Sharma, NH Vo, S Aditya, C Baral – … of the 3rd Workshop on EVENTS …, 2015 – aclweb.org … Furthermore, many other tools are also used at various steps in the above mentioned modules, such as Named En- tity Tagging, WordNet database and Weka statistical classifier library (Witten et al., 1999). … 2007. Deep linguistic processing for spoken dialogue systems. … Cited by 1 Related articles All 13 versions

Using Summarization to Discover Argument Facets in Online Idealogical Dialog A Misra, P Anand, JF Tree, M Walker – aclweb.org … Amita Misra, Pranav Anand, Jean Fox Tree, and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High … regression problem and evaluate support vector regression and linear regres- sion for 10-fold cross validation using the Weka ma- chine … Related articles All 2 versions

The role of speakers and context in classifying competition in overlapping speech. SA Chowdhury, M Danieli, G Riccardi – INTERSPEECH, 2015 – sensei-conversation.eu … overlaps by the overlap- per’s intention is important for behavioral signal studies and for improving the quality of the spoken dialog system. … We trained our classification systems using Sequential Minimal Optimization (SMO), a support vector machine implementation of weka [31 … Cited by 5 Related articles All 4 versions

“So, which one is it?” The effect of alternative incremental architectures in a high-performance game-playing agent M Paetzel, R Manuvinakurike, D DeVault – 16th Annual Meeting of the …, 2015 – aclweb.org … 2009. The weka data mining software: An update. SIGKDD Explor. Newsl., 11 (1): 10–18, November. … 2013. Demonstration of the par- lance system: a data-driven, incremental, spoken dialogue system for interactive search. Proc SIG- DIAL, pages 154–156. … Cited by 2 Related articles All 13 versions

Pragmatics and Dialogue Acts AC Fang, J Cao – Text Genres and Registers: The Computation of …, 2015 – Springer … concentrated how to improve the performance of automatic DA identification and annotation for better application to dialogue systems , and yet … Naïve Bayes Multinomial Classifier , which is available from Waikato Environment for Knowledge Analysis , known as Weka (Hall et al. …

Annotating and categorizing competition in overlap speech SA Chowdhury, M Danieli… – Acoustics, Speech and …, 2015 – ieeexplore.ieee.org … interest in understanding more about this phenomenon is shown with the aim of improving the quality and natural- ness of spoken dialog systems. … For the automatic feature selection we used Correlation- based Feature Selection (CFS) [29] and its implementation in Weka [30]. … Cited by 7 Related articles All 5 versions

A Machine Learning Approach to Dialogue Act Classification in Human-Robot Conversations: Evaluation of dialogue act classification with the robot Furhat and an … N Olofsson, N Fakih – 2015 – diva-portal.org … 14 3.4.1 WEKA . . … For instance, such variables could be facial expressions, head nods or gestures. This can also be applied to dialogue systems. Such a system, which is able to collect information from more than one interactive channel, is called a multimodal dialogue system. … Related articles

Towards Addressing the Winograd Schema Challenge-Building and Using a Semantic Parser and a Knowledge Hunting Module. A Sharma, NH Vo, S Aditya, C Baral – IJCAI, 2015 – researchgate.net … Weka: Practical machine learning tools and techniques with java implementations. AI Tools SeminarUniversity of Saarland, WS, 6(07), 2007. … Integrating linguistic and do- main knowledge for spoken dialogue systems in multiple domains. In Proc. … Cited by 10 Related articles All 12 versions

Posteriori restoration of turn-taking and ASR results for incorrectly segmented utterances K Komatani, N Hotta, M NAKANO – IEICE TRANSACTIONS on …, 2015 – jstage.jst.go.jp … This means that the sys- tem starts responding while the user is still speaking. Basi- cally, spoken dialogue systems start responding when they receive an ASR result. … Decision trees are built by J48 with its default parameter in machine learning software Weka †† . … Cited by 2 Related articles All 6 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 … on other kinds of corpus are also reported, eg e-mails (Mohammad & Yang, 2011), novels (Mohammad, 2011) and Japanese dialog systems (Tokuhisa, Inui, & … Here ? 2 -test, which is implemented by Weka (Hall et al., 2009), together with word frequency and PMI are adopted. … Cited by 12 Related articles All 3 versions

Prosodic classification of discourse markers V Cabarrão, H Moniz, J Ferreira, F Batista, I Trancoso… – markers, 2015 – inesc-id.pt … In order to achieve a baseline for further experiments, we also applied a ZeroR method from Weka, which selects the most … trained with other structural metadata events, which will result in enriched automatic transcriptions, and to integrate the classifiers in dialogue systems. … Related articles All 5 versions

Fusion of sentiment analysis and emotion recognition to model the user’s emotional state D Griol, JM Molina… – Information Fusion (Fusion …, 2015 – ieeexplore.ieee.org … This is the case of most spoken dialog systems, in which a baseline algorithm which always chooses “neutral” would have a very high accuracy … algorithm, a genetic search, and a ranking filter using the default values of their respective parameters provided by the Weka toolkit. … Cited by 1 Related articles All 2 versions

Evolutionary feature selection for emotion recognition in multilingual speech analysis C Brester, E Semenkin, I Kovalev… – … (CEC), 2015 IEEE …, 2015 – ieeexplore.ieee.org … A. Problem Definition One of the obvious ways to improve the intellectual abilities of spoken dialogue systems is related to their personalization. … [19] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, IH Witten, “The WEKA Data Mining Software: An Update”, SIGKDD … Cited by 5 Related articles All 3 versions

Recognizing emotions in dialogues with acoustic and lexical features L Tian, JD Moore, C Lai – Affective Computing and Intelligent …, 2015 – ieeexplore.ieee.org … system? We plan to work on this question in the future if we have an available dialogue system to apply our emotion recognition models to. … fitting. 1) SVM: Our SVM models were built with the Lib- SVM [39] classifier using WEKA [40]. … Related articles All 8 versions

Improved multi-kernel SVM for multi-modal and imbalanced dialogue act classification Y Zhou, X Cui, Q Hu, Y Jia – Neural Networks (IJCNN), 2015 …, 2015 – ieeexplore.ieee.org … our recent research results show that the accent of an utterance is also essential to determine the DA tags in a Chinese dialogue system [5]. While in … All experiments are conducted with MATLAB 2011b and weka 7.1 on a computer running Windows 7 with 4GB main memory. … Cited by 1 Related articles All 2 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 …

Unsupervised assistive and adaptive intelligent agent in smart environment S Pais, J Casal, R Ponciano… – Proceedings of the …, 2015 – academia.edu … Indeed, the development of a spoken dialogue system requires the integration of several components of the spoken language technology, like speech … algorithm we use for test and evaluating the performance of algorithms, we use the open source data mining tool Weka. … Cited by 2 Related articles All 4 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 . . . . . … This approach to the resolution of NSUs has been the basis of several implementations of dialogue systems handling the resolution of NSUs such as Ginzburg et al. (2007) and Purver (2006). … Cited by 1 Related articles All 15 versions

Judging the quality of automatically generated gap-fill question using active learning NB Niraula, V Rus – Proceedings of the Tenth Workshop on …, 2015 – anthology.aclweb.org … Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H Witten. 2009. The weka data mining software: an update. ACM SIGKDD explorations newsletter, 11 (1): 10–18. … 2015. Rapidly scal- ing dialog systems with interactive learning. 206 Cited by 2 Related articles All 10 versions

An Approach to Sentiment Analysis for Mobile Speech Applications D Griol, JM Molina, A Sanchis, Z Callejas – International Workshop on …, 2015 – Springer … Despite its benefits, the recognition of emotions in dialog systems presents important challenges which are still unresolved. … of a forward selection algorithm, a genetic search, and a ranking filter using the default values of their respective parameters provided by the Weka toolkit. … Related articles All 2 versions

Laughter detection for on-line human-robot interaction M Tahon, L Devillers – Cough, 2015 – marietahon.noath.net … In the second phase, the subject would interact with the dialog system designed to induce emotions by projection: a daily situation with an … Automatic classification is performed with the Weka plat- form2 with SMO function, RBF kernel and non optimized parameters (c = 2 and ? … Cited by 2 Related articles All 3 versions

Estimating response obligation in multi-party human-robot dialogues T Sugiyama, K Funakoshi, M Nakano… – … ), 2015 IEEE-RAS …, 2015 – ieeexplore.ieee.org … spaces [3], [4]. Bohus and Horvitz [5], [6] built a model for managing engagement [7] in multi-party dialogues and devel- oped a spoken dialogue system for a conversational robot to give directions to a … To train and evaluate, we used the machine learning software Weka ver. … Cited by 2 Related articles All 2 versions

Harnessing Twitter Big Data for Automatic Emotion Identification R Rajeswari – iarjset.com … The drawback of ” WEKA Data Mining Software: An Update” is considering running time, there is no longer a major disadvantage compared to … A data-oriented method for gathering the emotion of a speaker conversing with a dialog system from the semantic content of a … Related articles

Emotion recognition in spontaneous and acted dialogues L Tian, JD Moore, C Lai – Affective Computing and Intelligent …, 2015 – ieeexplore.ieee.org … In a virtual agent dialogue system, the ability to recognize and express emotions can make the agent appear more natural and believable to its human dialogue partner. … 1) SVM: Our SVM models [25] were built with the Lib- SVM [38] classifier using WEKA [39]. … Cited by 5 Related articles All 12 versions

Constructive feedback, thinking process and cooperation: assessing the quality of classroom interaction. T Sousa, L Flekova, M Mieskes, I Gurevych – INTERSPEECH, 2015 – ukp.tu-darmstadt.de … freely available tools, such as the TreeTagger [16], and Support Vector Machines (SVM- SMO) included in Weka [17], in … mond, “Intrinsic and extrinsic evaluation of an automatic user disengagement detector for an uncertainty-adaptive spoken dialogue system,” in Proceedings … Related articles All 4 versions

Towards Classification of Engagement in Human Interaction with Talking Robots Y Huang, C Elias, JP Cabral, A Nautiyal… – … Conference on Human- …, 2015 – Springer … References. 1. Bohus, D., Horvitz, E.: Learning to predict engagement with a spoken dialog system in open-world settings. … Turkey (2012). 13. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, IH: The WEKA data mining software: an update. SIGKDD Explor. … Related articles

A proposal for the development of adaptive spoken interfaces to access the Web D Griol, JM Molina, Z Callejas – Neurocomputing, 2015 – Elsevier … Abstract. Spoken dialog systems have been proposed as a solution to facilitate a more natural human–machine interaction. In this paper, we … 94]. 3. Proposed framework to develop adaptive spoken dialog systems. Fig. 1 shows the … Cited by 1 Related articles All 3 versions

Prediction of relevant biomedical documents: a human microbiome case study P Thompson, JC Madan… – BioData …, 2015 – biodatamining.biomedcentral.com … Lancaster’s evaluation of the National Library of Medicine’s Medical Literature Analsyis and Retrieval System (MEDLARS) [23] and Saracevic’s own evaluations of the DIALOG system [24–26 … For our machine learning experiments we used the WEKA machine learning toolkit [37 … Related articles All 15 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, customer … For our experiments, we created one-versus-all classifiers for each of the six basic emotions using Weka (Hall et al. … Cited by 64 Related articles All 8 versions

State of the Research in Human Language Technology K Megerdoomian – Citeseer … morphological analysis. Another trend is the use of discourse analytics, especially in dialogue systems and Automatic Speech Recognition (ASR) applications. The … publications. 3 http://www.cs.waikato.ac.nz/ml/weka/ research and … Related articles All 6 versions

Big data driven natural language processing research and applications V Gudivada, D Rao, V Raghavan – Big Data Analytics, 2015 – books.google.com … These results are used in other tasks such as co-reference resolution, word-sense disambiguation, semantic parsing, question answering, dialog systems, textual entailment, information extraction, information retrieval, and text summarization. … Cited by 7 Related articles

Automatic evaluation of voice quality using text-based laryngograph measurements and prosodic analysis T Haderlein, C Schwemmle, M Döllinger… – … methods in medicine, 2015 – hindawi.com … In this study, the sequential minimal optimization algorithm (SMO) [30] of the Weka toolbox [31] was applied for this purpose. … 2.6. Human-Machine Correlation. Statistical analysis was performed using Weka and in-house programs. … Cited by 2 Related articles All 14 versions

A time series interaction analysis method for building predictive models of learners using log data C Brooks, C Thompson, S Teasley – Proceedings of the fifth international …, 2015 – dl.acm.org … matching [6] or tutors based on dialogue systems [12]. … To address these questions, we formed predictive mod- els with J48 decision trees using the Weka toolkit [13] for 4 different Michigan MOOCs offered on the Coursera plat- form. … Cited by 9 Related articles

Hierarchical reinforcement learning for situated natural language generation N Dethlefs, H Cuayáhuitl – Natural Language Engineering, 2015 – Cambridge Univ Press … generation for interactive systems (Lemon 2011). Rieser, Lemon and Liu (2010) apply RL to information presentation in a spoken dialogue system that gives restaurant recommendations to users. A particular focus is on whether … Cited by 11 Related articles All 8 versions

Social Media Mining with Natural Language Processing M Abdul-Mageed, M Dickinson – 2015 – scholarworks.iu.edu … conversational agents / dialogue systems ? machine translation … www.nltk.org/ ? Illinois tools: http://cogcomp.cs.illinois.edu/page/software ? DKPro: https://www.ukp.tu-darmstadt.de/research/ current-projects/dkpro/ ? Also includes a text classification tool built on top of weka …

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 … 1]. Speech emotion recognition has also been used in call center applications and mobile communication [2]. Some works tried to incorporate spoken dialogue system technology and service robots. Psychologists believe that … Related articles All 2 versions

Culture Clubs Processing Speech by Deriving and Exploiting Linguistic Subcultures DG Brizan – 2015 – ai2-s2-pdfs.s3.amazonaws.com … fields. A dialogue system could be created from the speech signals of one linguistic subculture and could generate prompts to the human interlocutor using text-to-speech (TTS). … SCAN) [10] and spectral clustering [76] as implemented in Weka [45], in scikit-learn [81]. Clustering … Related articles All 3 versions

What goes around comes around: learning sentiments in online medical forums V Bobicev, M Sokolova, M Oakes – Cognitive Computation, 2015 – Springer … Study of affect and social aspects in online communication is preliminary steps for creation of affective dialogue system in which text-based system–user communication … We applied Naïve Bayes (NB), NBText, NBMultinomial, SVM, Decision Trees and KNN from the WEKA toolkit … Cited by 6 Related articles All 3 versions

SENSEI Coordinator M Kabadjov, EA Stepanov, F Celli, SA Chowdhury… – sensei-conversation.eu … applications of DA analysis is quite wide and includes conversa- tion summarization (both spoken and written), dialogue systems, etc.; and … classification model is trained using Sequential Minimal Optimisation (SMO), a support vector machine implementation of weka [20] using … Related articles

Combining acoustic and visual features to detect laughter in adults’ speech. H Rao, Z Ye, Y Li, MA Clements, A Rozga, JM Rehg – AVSP, 2015 – researchgate.net … 5. Results A random forest (RF) classifier with 100 trees was trained using WEKA [21] on the speech and laughter samples. … 37, no. 5, p. 715, 1979. [2] J. Tepperman, D. Traum, and S. Narayanan, “” yeah right”: Sarcasm recognition for spoken dialogue systems,” in Ninth In … Related articles All 2 versions

Speech emotion recognition using SVM with thresholding fusion S Gupta, A Mehra – Signal Processing and Integrated …, 2015 – ieeexplore.ieee.org … Various types of communication system such as automatic answering system, dialogue system and human like robot can apply the emotion recognition and classification … [21] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann and IH Witten, “The WEKA data mining … Cited by 2 Related articles All 2 versions

Extracting sentiment from healthcare survey data: An evaluation of sentiment analysis tools D Georgiou, A MacFarlane… – … Conference (SAI), 2015, 2015 – ieeexplore.ieee.org … service. The commercial tools were Semantria and TheySay and the non- commercial tools were WEKA and Google Prediction API. … response. TABLE V. PROCEDURE FOLLOWED TO ANALYSE SENTIMENT BY WEKA WEKA Procedure … Cited by 1 Related articles All 2 versions

Extracting Sentiment from Healthcare Survey Data D Georgiou, A MacFarlane, T Russell-Rose – researchgate.net … service. The commercial tools were Semantria and TheySay and the non- commercial tools were WEKA and Google Prediction API. … tools). The non-commercial tools used were WEKA (version 3.7.10) and Google Prediction API. … Related articles

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 … 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 4 Related articles All 10 versions

Literature review for Deception detection G An – 2015 – gc.cuny.edu Page 1. Literature review for Deception detection by Guozhen An A Second Exam submitted to the Graduate Faculty in Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy, The City University of New York. 2015 Page 2. … Related articles All 3 versions

Supervised machine learning techniques to detect timeml events in french and english B Arnulphy, V Claveau, X Tannier, A Vilnat – International Conference on …, 2015 – Springer … 1 Introduction. Extracting events from texts is a keystone for many applications concerned with information access (question-answering systems, dialog systems, text mining…). … Concerning the DTs, we use the WEKA [10] implementation of C4.5 [22]. … Cited by 1 Related articles All 8 versions

Succeeding metadata based annotation scheme and visual tips for the automatic assessment of video aesthetic quality in car commercials F Fernández-Martínez, AH García… – Expert Systems with …, 2015 – Elsevier In this paper, we present a computational model capable to predict the viewer perception of car advertisements videos by using a set of low-level video descript. Cited by 3 Related articles All 8 versions

Affect detection from non-stationary physiological data using ensemble classifiers O AlZoubi, D Fossati, S D’Mello, RA Calvo – Evolving Systems, 2015 – Springer … A down-sampling procedure, WEKA’s SpreadSubsample which produces a random sub-sample of a dataset, was applied to obtain a balanced distribution of classes. … 2009). The WEKA machine learning software (Witten and Frank 2005) and PRTools 4.0 (Heijden et al. … Cited by 7 Related articles All 6 versions

RoboCHAIR: Creative Assistant for Question Generation and Ranking S Pollak, B Lesjak, J Kranjc… – Computational …, 2015 – ieeexplore.ieee.org … [8]. AQG technologies can be used in question-answering (eg [9]), dialogue systems (eg [10]), educational applications or intelligent tutoring systems (eg [11], [12]). … The Weka machine learning software was used to perform several experiments. … Related articles

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 15 Related articles All 20 versions

GUDM: Automatic generation of unified datasets for learning and reasoning in healthcare R Ali, MH Siddiqi, M Idris, T Ali, S Hussain, EN Huh… – Sensors, 2015 – mdpi.com Next Article in Journal Augmented Robotics Dialog System for Enhancing Human–Robot Interaction. Previous Article in Journal Using Hand Grip Force as a Correlate of Longitudinal Acceleration Comfort for Rapid Transit Trains. … Cited by 1 Related articles All 15 versions

The eras and trends of automatic short answer grading S Burrows, I Gurevych, B Stein – International Journal of Artificial …, 2015 – Springer … This can be supported by a machine learning toolkit such as Weka (Hall et al. 2009). Features involving bag-of-words and n-grams are typical of this category, as are decision trees and support vector machines as representative learning algorithms. e-Examiner (14). … Cited by 33 Related articles All 8 versions

Similarity computation using semantic networks created from web-harvested data E Iosif, A Potamianos – Natural Language Engineering, 2015 – Cambridge Univ Press Page 1. Natural Language Engineering 21 (1): 49–79. c Cambridge University Press 2013 doi:10.1017/S1351324913000144 49 Similarity computation using semantic networks created from web-harvested data ELIAS IOSIF … Cited by 24 Related articles All 4 versions

From simulated speech to natural speech, what are the robust features for emotion recognition? Y Li, L Chao, Y Liu, W Bao, J Tao – Affective Computing and …, 2015 – ieeexplore.ieee.org … Three feature selection methods implemented in Weka are utilized in this work. The feature … 835-838. [14] D. Küstner, R. Tato, T. Kemp, and B. Meffert, “Towards real life applications in emotion recognition,” in Affective Dialogue Systems, ed: Springer, 2004, pp. 25-35. … Cited by 2 Related articles All 7 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, information retrieval, and text categorization itself. … These experiments were aided by Weka, a popular data mining tool that contains built-in functions for the algorithms of interest … Related articles All 4 versions

[BOOK] Text Genres and Registers: The Computation of Linguistic Features CA Fang, J Cao – 2015 – books.google.com … The au- thors would also like to acknowledge supports received from the Dialogue Systems Group, Department of Linguistics and Translation, and the Halliday Centre for In- telligent Applications of Language … 51 3.5.2 Weka….. … Related articles All 3 versions

Robust object classification in underwater sidescan sonar images by using reliability-aware fusion of shadow features N Kumar, U Mitra, SS Narayanan – IEEE Journal of Oceanic …, 2015 – ieeexplore.ieee.org … is partly similar to the idea of garbage modeling commonly used in automatic speech recognition tasks [12], [13], where these models are used to identify out of vo- cabulary (OOV) words in dialog systems [14] or … The fusion methods are im- plemented via the WEKA toolkit [34]. … Cited by 5 Related articles All 3 versions

Open-Source Media Interpretation By Large Feature-Space Extraction F Eyben, F Weninger, M Wöllmer, B Schuller – academia.edu … These formats include PCM WAVE for audio files, CSV (Comma Separated Value, spreadsheet format) and ARFF (Weka Data Mining) for text-based … eu) and is used there as the acoustic emotion recogni- tion engine and keyword spotter in a real-time affective dialogue system. … Related articles

Automatic Speech Emotion Recognition-Feature space Dimensionality and Classification Challenges AKF Al-Talabani – 2015 – researchgate.net … mode of communication. Building a dialogue system for natural speech is becoming an interesting area of research that could benefit from SER. Most existing applications with regard to automatic dialogue systems are reported to be restricted Page 17. 3 … Related articles All 2 versions

Automated quality assurance of non-functional requirements for testability A Rashwan – 2015 – spectrum.library.concordia.ca Page 1. AUTOMATED QUALITY ASSURANCE OF NON-FUNCTIONAL REQUIREMENTS FOR TESTABILITY ABDERAHMAN RASHWAN A THESIS IN THE DEPARTMENT OF COMPUTER SCIENCE AND SOFTWARE ENGINEERING … Cited by 2 Related articles All 3 versions

Within and cross-corpus speech emotion recognition using latent topic model-based features M Shah, C Chakrabarti, A Spanias – … Journal on Audio, Speech, and Music …, 2015 – Springer … it an ideal choice for improving human-machine interaction [1]. Speech-based emotion recognition is applicable to automatic speech recognition (ASR), spoken dialog systems (SDS) [2 … Classification is performed via a linear kernel SVM/SVR trained using the WEKA toolkit [48]. … Cited by 4 Related articles All 5 versions

[BOOK] Biometric and Intelligent Decision Making Support A Kaklauskas – 2015 – Springer Page 1. Intelligent Systems Reference Library 81 Arturas Kaklauskas Biometric and Intelligent Decision Making Support Page 2. Intelligent Systems Reference Library Volume 81 Series editors Janusz Kacprzyk, Polish Academy … Cited by 15 Related articles All 6 versions

Automatic Personality Estimation T Polzehl – Personality in Speech, 2015 – Springer … More specifically, the so called Sequential-Minimal-Optimization, (SMO) algorithm as implemented in the WEKA toolkit Witten and Frank (2005) is applied in this work. In principle a solution is obtained by using Lagrangian multipliers in the dual form of the problem. … Related articles

Sentiment Analysis of M&S Customers Reviews A Alharbi – 2015 – vlebb.leeds.ac.uk … Weka.3.6 …………… 27 4.3.1. StringToWordVector Weka filter …………… 28 … The following software is used in this project: Matlab version R2014b for data pre- processing purposes and Weka toolkit version 3.6. … Related articles

[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 Page 1. Obdulia Pichardo Lagunas Oscar Herrera Alcántara Gustavo Arroyo Figueroa (Eds.) Advances in Artificial Intelligence and Its Applications 14th Mexican International Conference on Artificial Intelligence, MICAI 2015 … Related articles All 4 versions

Question Generation from Knowledge Graphs D Seyler, K Berberich, G Weikum – 2015 – pubman.mpdl.mpg.de … 15 2.3.4 Normalizing and Standardizing Data . . . . . 18 2.3.5 Cross Validation . . . . . 19 2.3.6 Weka . . . . . 19 2.4 Processing Large Datasets . . . . . … Related articles

Paralinguistic event detection in children’s speech H Rao – 2015 – smartech.gatech.edu Page 1. PARALINGUISTIC EVENT DETECTION IN CHILDREN’S SPEECH A Thesis Presented to The Academic Faculty by Hrishikesh Rao In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the School of Electrical and Computer Engineering … Related articles

Sarcasm detection on twitter: A behavioral modeling approach A Rajadesingan, R Zafarani, H Liu – … on Web Search and Data Mining, 2015 – dl.acm.org Page 1. Sarcasm Detection on Twitter: A Behavioral Modeling Approach Ashwin Rajadesingan, Reza Zafarani, and Huan Liu Computer Science and Engineering Arizona State University {arajades, reza, huan.liu}@asu.edu … Cited by 36 Related articles All 5 versions

Novel Methods for Text Preprocessing and Classification T Gasanova – 2015 – deutsche-digitale-bibliothek.de … 87 2.17 Co-Operation of Biology Related Algorithms (COBRA) . . . . 89 3.1 Overview of Spoken Dialogue Systems . . . . . 105 4.1 Common diagramm of text preprocessing and text classification . . . . . … Related articles

Stuck and frustrated or in flow and happy: Sensing developers’ emotions and progress SC Müller, T Fritz – … Engineering (ICSE), 2015 IEEE/ACM 37th …, 2015 – ieeexplore.ieee.org Page 1. Stuck and Frustrated or In Flow and Happy: Sensing Developers’ Emotions and Progress Sebastian C. Müller, Thomas Fritz Department of Informatics, University of Zurich, Switzerland 1smueller, fritzl@ifi.uzh.ch Abstract … Cited by 20 Related articles All 2 versions

Evolving the Ecosystem of Personal Behavioral Data JS Wiese – 2015 – repository.cmu.edu Page 1. Carnegie Mellon University Research Showcase @ CMU Dissertations Theses and Dissertations Fall 9-2015 Evolving the Ecosystem of Personal Behavioral Data Jason Stampfer Wiese Carnegie Mellon University Follow … Related articles

[BOOK] Prominent feature extraction for sentiment analysis B Agarwal, N Mittal – 2015 – books.google.com … 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 … Cited by 8 Related articles All 9 versions