WEKA & Dialog Systems 2017


Resources:

  • halef .. open source vxml-based spoken dialog system
  • talkingtothecrowd.org .. a google hangouts chatbot powered by crowdsourcing
  • weka .. collection of machine learning algorithms for data mining

Wikipedia:

References:

See also:

100 Best Weka Tutorial Videos | Machine Learning | WikipediaMiner


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. High … regression problem and evaluate support vector regression and linear regres- sion for 10-fold cross validation using the Weka ma- chine …

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, Santa Cruz maw|amitamisra@soe.ucsc … tion and then test on our mixed-topic test set, using the Weka learners for Random forest and J48 Tree …

Evorus: A crowd-powered conversational assistant that automates itself over time
THK Huang, JC Chang, S Swaminathan… – Adjunct Publication of …, 2017 – dl.acm.org
… chatterbots. Our next step is to include task-oriented dialog systems into the mix to allow Evorus to better handle assistance in domains in which these systems work well … 2008. The Weka classifier works with version 1.33 of LIBLINEAR …

User-Adaptive A Posteriori Restoration for Incorrectly Segmented Utterances in Spoken Dialogue Systems
K Komatani, N Hotta, S Sato… – Dialogue & Discourse, 2017 – dad.uni-bielefeld.de
… We used the SMO module in Weka (version 3.6.9) (Hall et al., 2009) as an SVM implementation … 4.3 Target Data Our target data were collected by our spoken dialog system that introduces world heritage sites (Nakano et al., 2011) …

A Data-Driven Approach to Dialog Structure Modeling
D Griol, A Sanchis, JM Molina – … Joint Conference SOCO’17-CISIS’17 …, 2017 – Springer
… The C4.5 decision tree learning algorithm has been used to learn this classification model, using the Weka machine learning software for … We have applied our proposal to the problem solving domain of a practical spoken dialog system, which acts as a customer support service …

Using acoustic paralinguistic information to assess the interaction quality in speech-based systems for elderly users
H Pérez-Espinosa, J Martínez-Miranda… – International Journal of …, 2017 – Elsevier
… Georgila et al. (2008) created a corpus of interactions made by older and young users using a Wizard-of-Oz (WoZ)-based dialogue system, where they designed and annotated this corpus to examine the impact of cognitive aging on user interactions with this type of system …

Significance of Interaction Parameter Levels in Interaction Quality Modelling for Human-Human Conversation
A Spirina, A Skorokhod, T Karaseva… – … Conference on Text …, 2017 – Springer
… Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutmann, P., Witten, IH: The WEKA data mining software: an update. SIGKDD Explor … In: Proceedings of the 7th International Workshop on Spoken Dialogue Systems (IWSDS) (2016)Google Scholar. 24 …

Could Emotions Be Beneficial for Interaction Quality Modelling in Human-Human Conversations?
A Spirina, W Minker, M Sidorov – International Conference on Text …, 2017 – Springer
… doi:10.1007/978-3-540-31865-1_25 CrossRefGoogle Scholar. 8. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutmann, P., Witten, IH: The WEKA data mining … In: Lee, GG, Kim, HK, Jeong, M., Kim, J.-H. (eds.) Natural Language Dialog Systems and Intelligent Assistants, pp …

Lexical Acquisition through Implicit Confirmations over Multiple Dialogues
K Ono, R Takeda, E Nichols, M Nakano… – Proceedings of the 18th …, 2017 – aclweb.org
… This is possible because our system is designed as a server-based dialogue system and can give implicit confirma- tion requests with the same predicted … tion 5. We applied logistic regression to them with the features listed in Table 2. We used the module in Weka (version 3.8.1 …

A Deep Learning approach to modeling competitiveness in spoken conversations
SA Chowdhury, G Riccardi – Acoustics, Speech and Signal …, 2017 – ieeexplore.ieee.org
… the other speaker the cues about the mutual understanding [6]. Over the years speech scientist studied overlaps to im- prove the quality of human-machine dialog systems and the … For the classification we use Support Vector Machine (SVMs) implementation of Weka [26] …

Towards a continuous speech corpus for banking domain automatic speech recognition
G Suciu, ?A Toma… – Speech Technology and …, 2017 – ieeexplore.ieee.org
… support services. Keywords—speech corpus; banking; dialogue system; automatic speech recognition. I … in [26]. The classifier was implemented using Weka [27] and trained using the MaRePhor phonetic dictionary [28]. The …

Analysis of Overlapping Speech and Emotions for Interaction Quality Estimation
A Spirina, O Vaskovskaia, M Sidorov – International Conference on …, 2017 – Springer
… In: Natural Language Dialog Systems and Intelligent Assistants, pp. 41–52 (2015)Google Scholar. 10 … 403–410 (2016)Google Scholar. 27. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutmann, P., Witten, IH: The weka data mining software: an update. SIGKDD Explor …

UAM’s participation at CLEF eRisk 2017 task: Towards modelling depressed bloggers
E Villatoro-Tello, G Ram?rez-de-la-Rosa… – pdfs.semanticscholar.org
… 4 http://www.cs.waikato.ac.nz/ml/weka/ Page 6 … 4. Á. Callejas-Rodr?guez, E. Villatoro-Tello, I. Meza, and G. Ram?rez-de-la Rosa, From Dialogue Corpora to Dialogue Systems: Generating a Chatbot with Teenager Personality for Preventing Cyber-Pedophilia, pp. 531–539 …

Analysis of Interaction Parameter Levels in Interaction Quality Modelling for Human-Human Conversation
A Spirina, O Vaskovskaia, T Karaseva… – … Conference on Speech …, 2017 – Springer
… the dialogue quality, especially the quality of interaction, is an essential part for improving the quality of spoken dialogue systems (SDSs) or … For our study we have relied on the following classification algorithms, which are implementedin in Rapidminer 1 and WEKA [14]: Kernel …

Dynamic Gesture Recognition for Social Robots
JC Castillo, D Cáceres-Domínguez… – … Conference on Social …, 2017 – Springer
… Cybern. Syst. 42(4), 215–245 (2011)CrossRefGoogle Scholar. 4. Alonso-Martín, F., Castro-González, A., Luengo, F., Salichs, M.: Augmented robotics dialog system for enhancing human-robot interaction … Holmes, G., Donkin, A., Witten, I.: WEKA: a machine learning workbench …

Artificial intelligence in e-learning
HA Harouni, E Hachem, C Ziti – Shaping the Future of ICT: Trends …, 2017 – books.google.com
… 1 The Predictive Model Page 172. 6.7. 2 Exploring Data and Weka 6.7. 2.1 Logistic Regression 6.7. 2.2 Decision Tree Algorithm J48 6.7. 2.3 IBk 6.7 … Take dialogue systems, for example, which determine the emotional state of the user using a dialogic strategy …

Learning lexico-functional patterns for first-person affect
L Reed, J Wu, S Oraby, P Anand, M Walker – arXiv preprint arXiv …, 2017 – arxiv.org
… We thus experiment with a number of baseline classifiers: the default SVM classi- fier from Weka with unigram features (Hall et al., 2005), a version of the NRC-Canada sentiment classifier (Mohammad et al., 2013), provided to us … Data-driven dialogue systems for social agents …

Situation Understanding for Turn-Taking in Human-Robot Dialogue
???? – 2017 – ir.library.osaka-u.ac.jp
… Chapter 1 provides this study’s background, and introduces a new architec- ture of spoken dialogue systems for humanoid robots in public spaces. Chapter 2 Page 5. ii … a social channel (human-like utterances and motions). 1.2 Architecture of Spoken Dialogue Systems for …

Words matter: automatic detection of teacher questions in live classroom discourse using linguistics, acoustics, and context
PJ Donnelly, N Blanchard, AM Olney, S Kelly… – Proceedings of the …, 2017 – dl.acm.org
… We explored a number of common machine learning classifiers using implementations from the WEKA toolkit [43]: Naïve Bayes, logistic regression, random forest, J48 decision tree, J48 with Bagging, Bayesian network, k- nearest neighbor (k = 7, 9, and 11) …

Functions of Silences towards Information Flow in Spoken Conversation
SA Chowdhury, E Stepanov, M Danieli… – Proceedings of the …, 2017 – aclweb.org
… ner. Generally, in a dialog system, silence is not acknowledged as a form of interaction, but rather its function in a conversation is seen as a “pause” or a “gap”. Whereas speech is viewed as the pri- mary carrier of information …

A Semi-Supervised Approach to Detecting Stance in Tweets
A Misra, B Ecker, T Handleman, N Hahn… – arXiv preprint arXiv …, 2017 – arxiv.org
… Amita Misra, Brian Ecker, Theodore Handleman, Nicolas Hahn and Marilyn Walker Natural Language and Dialogue Systems Lab University of … We ran experiments using the SemEval training as our development data with NaiveBayesMultinomial, SVM, and J48 from WEKA …

Reinforcement Learning Based Argument Component Detection
Y Gao, H Wang, C Zhang, W Wang – arXiv preprint arXiv:1702.06239, 2017 – arxiv.org
… We have tried using HAs-augmented features in some other SL algo- rithms (J48 decision tree, naive Bayes and random forest pro- vided in WEKA [Hall et al., 2009]), and we make similar ob- servations … The WEKA data mining software: an update …

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 …

Emotion Recognition from Speech
A Wendemuth, B Vlasenko, I Siegert, R Böck… – Companion …, 2017 – Springer
… Finally, this resulted in 1242 BoW features. Therefore we employed a feature ranking method to select the most informative ones. Using WEKA, we employed an information gain attribute evaluator in conjunction with a feature ranker as the search method …

THIN FILM ROUGHNESS OPTIMIZATION IN THE TIN COATINGS USING GENETIC ALGORITHMS
NURF FAUZI, ASM JAYA, MI JARRAH, H AKBAR… – Journal of Theoretical …, 2017 – jatit.org
… 2017 — Vol. 95. No. 24 — 2017. Full Text. Title: ONLINE PERFORMANCE DIALOGUE SYSTEM MODEL (e-DP): A REQUIREMENT ANALYSIS STUDY AT BATU PAHAT DISTRICT EDUCATION OFFICE. Author: ASRAR NAJIB …

Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform
I Steiner, SL Maguer – arXiv preprint arXiv:1712.04787, 2017 – arxiv.org
… MaryTTS as a component into more complex applications, such as TTS web services, accessibility software, or spoken dialog systems (SDSs) … the lexicon is automatically compiled into a finite state transducer (FST)-based representation, relying in part on the WEKA toolkit (Hall …

Analyzing the Impact of Different Feature Queries in Active Learning for Social Robots
V Gonzalez-Pacheco, M Malfaz… – International Journal of …, 2017 – Springer
… 4], and Sequential Minization Optimization (SMO) [19], to compute three different classifiers. These algorithms are freely available in the Weka Framework [10]. Since our pur- pose is not to develop or compare learning algorithms …

Subjective Text Mining for Arabic Social Media
NFB Hathlian, AM Hafez – … Journal on Semantic Web and Information …, 2017 – igi-global.com
… For the classification phase, we trained our sentiment classifier by applying the Naïve Baysian algorithm in Weka Suite Software version 3.6.13 … Hijjawi, M., & Bander, Z. (2011). An Arabic Stemming Approach using Machine Learning with Arabic Dialogue System …

Annotating and modeling empathy in spoken conversations
F Alam, M Danieli, G Riccardi – Computer Speech & Language, 2017 – Elsevier
Empathy, as defined in behavioral sciences, expresses the ability of human beings to recognize, understand and react to emotions, attitudes and beliefs of other.

Automatically Classifying User Engagement for Dynamic Multi-party Human–Robot Interaction
ME Foster, A Gaschler, M Giuliani – International Journal of Social …, 2017 – Springer
… For this initial experiment in trained classification, we used the Weka data mining toolkit [27] to train a range of supervised-learning classifiers on this corpus, using a set of classifiers designed to provide good coverage of different classification styles …

Improving the understanding of spoken referring expressions through syntactic-semantic and contextual-phonetic error-correction
I Zukerman, A Partovi – Computer Speech & Language, 2017 – Elsevier
… For example, a research prototype of a spoken slot-filling dialogue system reported a Word Error Rate (WER) of 13.8% when using “a generic … Naïve Bayes (NB) (Domingos and Pazzani, 1997), and Support Vector Machines (SVMs) (Vapnik, 1998) (cs.waikato.ac.nz/ml/weka/) …

Analyzing User Emotions via Physiology Signals
B Myroniv, CW Wu, Y Ren, A Christian, E Bajo… – ikelab.net
… mentalhealth/consequences/ [12] Weka 3: Data Mining Software in Java, http : //www.cs.waikato. ac.nz/ml/weka/ [13] Ralf … Peter Schaich, Jason Williams,“Emotion Recognition Using Biosen- sors: First Steps towards an Automatic System,” Affective Dialogue Systems, Tutorial and …

Fully automatic analysis of engagement and its relationship to personality in human-robot interactions
H Salam, O Celiktutan, I Hupont, H Gunes… – IEEE …, 2017 – ieeexplore.ieee.org
Page 1. Received July 21, 2016, accepted August 30, 2016, date of publication September 30, 2016, date of current version March 6, 2017. Digital Object Identifier 10.1109/ACCESS. 2016.2614525 Fully Automatic Analysis of Engagement and Its Relationship to Personality in …

Sarcasm Identification on Twitter: A Machine Learning Approach
A Onan – Computer Science On-line Conference, 2017 – Springer
… The experimental analysis is performed with the machine learning toolkit WEKA (Waikato Environment for Knowledge Analysis) version 3.9, which is an open-source … Tepperman, J., Traum, DR, Narayanan, S.: “yeah right”: sarcasm recognition for spoken dialogue systems …

Harnessing cognitive features for sarcasm detection
A Mishra, D Kanojia, S Nagar, K Dey… – arXiv preprint arXiv …, 2017 – arxiv.org
… (2013) and Joshi et al. (2015) on our dataset. Using Weka (Hall et al., 2009) and LibSVM (Chang and Lin, 2011) APIs, we implement the following classifiers: • Näive Bayes classifier • Support Vector Machines (Cortes and Vap- nik, 1995) with default hyper-paramaters …

Investigating neural architectures for short answer scoring
B Riordan, A Horbach, A Cahill, T Zesch… – Proceedings of the 12th …, 2017 – aclweb.org
… It consists of two subsets: Beetle, with student responses from interacting with a tutorial dialogue system, and SciEntsBank (SEB) with science assessment … baseline is based on DkPro TC (Daxenberger et al., 2014) and relies on support vector classification using Weka (Hall et al …

Monitoring disaster impact: detecting micro-events and eyewitness reports in mainstream and social media
H Tanev, V Zavarella, J Steinberger – idl.iscram.org
… Athanasopoulou, G., Klasinas, I. , Georgiladakis, S., Iosif, E. and Potamianos, A. (2014) Using lexical, syntactic and semantic features for non-terminal grammar rule induction in Spoken Dialogue Systems, IEEE Spoken Language … The WEKA data mining software: an update …

Foundations of Intelligent Systems: 23rd International Symposium, ISMIS 2017, Warsaw, Poland, June 26-29, 2017, Proceedings
M Kryszkiewicz, A Appice, D ?l?zak, H Rybinski… – 2017 – books.google.com
Page 1. Marzena Dominik Kryszkiewicz S´le?zak · Henryk · Annalisa Rybinski Appice Andrzej Skowron · Zbigniew W. Ras´ (Eds.) Foundations of Intelligent Systems 23rd International Symposium, ISMIS 2017 Warsaw, Poland, June 26–29, 2017 Proceedings 123 Page 2 …

SingularityNET: A decentralized, open market and inter-network for AIs
B Goertzel, S Giacomelli, D Hanson, C Pennachin… – 2017 – icotokn.com
… Neural net tools such as Caffe, Keras, Gluon, Tensorflow, Mxnet, DL4J and others; • generic machine learning toolkits such as Apache Singa and Mahout and Spark MLlib, Shogun, Oryx2, Waffles, WEKA and MOA; • Bayesian learning frameworks such as BCM, BAT and MLN; …

Classifying a Person’s degree of accessibility from natural body language during social human–robot interactions
D McColl, C Jiang, G Nejat – IEEE transactions on cybernetics, 2017 – ieeexplore.ieee.org
… The five features are then utilized to classify each skin region. The WEKA data mining software [47] was utilized to determine the most appropriate machine learning technique to utilize for classifying head and/or lower arm configurations …

SmaCH: an infrastructure for smart cultural heritage environments
A Chianese, F Piccialli – … Journal of Ad Hoc and Ubiquitous …, 2017 – inderscienceonline.com
… Once the user have completed the questionnaire, these information are transferred to the Profiling Module and processed by a classifier by means of Weka API (http://www.cs.waikato.ac.nz/ml/ index.html), a software module that performs several standard Machine Learning …

Computational modeling of turn-taking dynamics in spoken conversations
SA Chowdhury – 2017 – eprints-phd.biblio.unitn.it
Page 1. PhD Dissertation International Doctorate School in Information and Communication Technologies DISI – University of Trento COMPUTATIONAL MODELING OF TURN-TAKING DYNAMICS IN SPOKEN CONVERSATIONS Shammur Absar Chowdhury Advisor: Prof …

Emotion Actuator: Embodied emotional feedback through electroencephalography and electrical muscle stimulation
M Hassib, M Pfeiffer, S Schneegass, M Rohs… – Proceedings of the 2017 …, 2017 – dl.acm.org
… Ta- ble 3 depicts the results of our participant-dependent classifi- cation which was done using Weka4. Results show that clas- sification using features from the EPOC affective suite and facial expressions is possible, with accuracies between 59.4% and 89.2 …

Subject-independent emotion recognition based on physiological signals: a three-stage decision method
J Chen, B Hu, Y Wang, P Moore… – BMC medical …, 2017 – bmcmedinformdecismak …
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Combining augmented statistical noise suppression and framewise speech/non-speech classification for robust voice activity detection
Y Obuchi – APSIPA Transactions on Signal and Information …, 2017 – cambridge.org
… 2) Toolkits The classifiers were trained using publicly available toolk- its. WEKA [29] was used for DT and SVM training, and Caffe [30] was used for CNN training … When we use WEKA for DT and SVM, we adopt the classifier ensemble approach …

A multi-agent framework to support user-aware conversational agents In an e-learning environment
M Procter – 2017 – dt.athabascau.ca
Page 1. ATHABASCA UNIVERSITY A MULTI-AGENT FRAMEWORK TO SUPPORT USER-AWARE CONVERSATIONAL AGENTS IN AN E-LEARNING ENVIRONMENT BY MICHAEL PROCTER A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES …

Automatic assessment of depression based on visual cues: A systematic review
A Pampouchidou, P Simos, K Marias… – IEEE Transactions …, 2017 – ieeexplore.ieee.org
Page 1. 1949-3045 (c) 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org …

Natural language generation in the context of multimodal interaction in Portuguese: Data-to-text based in automatic translation
JC Pereira – 2017 – ria.ua.pt
Page 1. Universidade de Aveiro Departamento de Electrónica, Telecomunicaç˜oes e Informática 2017 das Universidades de Aveiro, Minho e Porto Programa de Doutoramento em Informática José Casimiro Pereira Geraç˜ao de Linguagem Natural noÂmbito de …

Generating variations in a virtual storyteller
SM Lukin – 2017 – search.proquest.com
… 25. 2.2 Narrative and Dialogue Systems . . . . . 27 … 139. 5.17 Excerpts of different deaggregation condition in ablation test . . . . . 1406.1 Classication with SMO in Weka . . . . . 155 …

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