Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations
暂无分享,去创建一个
[1] Quan Hung Tran,et al. A Hierarchical Neural Model for Learning Sequences of Dialogue Acts , 2017, EACL.
[2] François Chollet,et al. Keras: The Python Deep Learning library , 2018 .
[3] A. Koller,et al. Speech Acts: An Essay in the Philosophy of Language , 1969 .
[4] Wolfgang Minker,et al. A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let’s Go Bus Information System , 2012, LREC.
[5] Ricardo Ribeiro,et al. A Multilingual and Multidomain Study on Dialog Act Recognition Using Character-Level Tokenization , 2019, Inf..
[6] Beatrice Santorini,et al. Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.
[7] Daniel Marcu,et al. The rhetorical parsing of unrestricted texts: a surface-based approach , 2000, CL.
[8] Jonathan Weese,et al. UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems , 2013, *SEMEVAL.
[9] José Camacho-Collados,et al. From Word to Sense Embeddings: A Survey on Vector Representations of Meaning , 2018, J. Artif. Intell. Res..
[10] Franck Dernoncourt,et al. Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks , 2016, NAACL.
[11] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[12] Elizabeth Shriberg,et al. The ICSI Meeting Recorder Dialog Act (MRDA) Corpus , 2004, SIGDIAL Workshop.
[13] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[14] Gholamreza Haffari,et al. A Latent Variable Recurrent Neural Network for Discourse Relation Language Models , 2016, ArXiv.
[15] Michael Ferguson,et al. Automatic Extraction of Cue Phrases for Cross-Corpus Dialogue Act Classification , 2010, COLING.
[16] Slav Petrov,et al. A Universal Part-of-Speech Tagset , 2011, LREC.
[17] Gholamreza Haffari,et al. A Latent Variable Recurrent Neural Network for Discourse Relation Language Models , 2016 .
[18] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[19] Luke S. Zettlemoyer,et al. Deep Contextualized Word Representations , 2018, NAACL.
[20] M. Rotaru. Dialog Systems ” class , Spring 2002-TERM PROJECT-Dialog Act Tagging using Memory-Based Learning , 2007 .
[21] Anne H. Anderson,et al. The Hcrc Map Task Corpus , 1991 .
[22] Mari Ostendorf,et al. A Dynamic Speaker Model for Conversational Interactions , 2019, NAACL.
[23] Elizabeth Shriberg,et al. Switchboard SWBD-DAMSL shallow-discourse-function annotation coders manual , 1997 .
[24] Tomas Mikolov,et al. Enriching Word Vectors with Subword Information , 2016, TACL.
[25] Shrikanth S. Narayanan,et al. Combining lexical, syntactic and prosodic cues for improved online dialog act tagging , 2009, Comput. Speech Lang..
[26] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[27] Cícero Nogueira dos Santos,et al. Learning Character-level Representations for Part-of-Speech Tagging , 2014, ICML.
[28] Jürgen Schmidhuber,et al. Dynamische neuronale Netze und das fundamentale raumzeitliche Lernproblem , 1990 .
[29] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[30] Yoon Kim,et al. Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.
[31] Christopher D. Manning. Computational Linguistics and Deep Learning , 2015, Computational Linguistics.
[32] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[33] Eduardo Lleida,et al. Design and acquisition of a telephone spontaneous speech dialogue corpus in Spanish: DIHANA , 2006, LREC.
[34] Jörg Tiedemann,et al. Parallel Data, Tools and Interfaces in OPUS , 2012, LREC.
[35] Yann LeCun,et al. Very Deep Convolutional Networks for Text Classification , 2016, EACL.
[36] Yoshua Bengio,et al. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling , 2014, ArXiv.
[37] L. Baum,et al. Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .
[38] Andreas Stolcke,et al. The ICSI Meeting Corpus , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[39] Pavel Král,et al. Dialogue Act Recognition Approaches , 2010, Comput. Informatics.
[40] Alec Radford,et al. Improving Language Understanding by Generative Pre-Training , 2018 .
[41] Yoav Goldberg,et al. A Primer on Neural Network Models for Natural Language Processing , 2015, J. Artif. Intell. Res..
[42] Rodney D. Nielsen,et al. Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network , 2016, COLING.
[43] Tomas Mikolov,et al. Advances in Pre-Training Distributed Word Representations , 2017, LREC.
[44] Omer Levy,et al. Dependency-Based Word Embeddings , 2014, ACL.
[45] Luke S. Zettlemoyer,et al. AllenNLP: A Deep Semantic Natural Language Processing Platform , 2018, ArXiv.
[46] Jun Zhao,et al. Recurrent Convolutional Neural Networks for Text Classification , 2015, AAAI.
[47] Norbert Reithinger,et al. Dia logue Acts in VERBMOBIL-2 Second Edition , 1997 .
[48] Jean Carletta,et al. Assessing Agreement on Classification Tasks: The Kappa Statistic , 1996, CL.
[49] John J. Godfrey,et al. SWITCHBOARD: telephone speech corpus for research and development , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[50] Deniz Yuret,et al. CharNER: Character-Level Named Entity Recognition , 2016, COLING.
[51] Yun Lei,et al. Using Context Information for Dialog Act Classification in DNN Framework , 2017, EMNLP.
[52] Elizabeth Shriberg,et al. Automatic dialog act segmentation and classification in multiparty meetings , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[53] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[54] Xiang Zhang,et al. Character-level Convolutional Networks for Text Classification , 2015, NIPS.
[55] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[56] Martín Abadi,et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , 2016, ArXiv.
[57] Phil Blunsom,et al. Recurrent Convolutional Neural Networks for Discourse Compositionality , 2013, CVSM@ACL.
[58] Ingrid Zukerman,et al. Preserving Distributional Information in Dialogue Act Classification , 2017, EMNLP.
[59] Peter E. Hart,et al. Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.
[60] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[61] Ricardo Ribeiro,et al. A Study on Dialog Act Recognition using Character-Level Tokenization , 2018, AIMSA.
[62] Fabrizio Sebastiani,et al. Distributional term representations: an experimental comparison , 2004, CIKM '04.
[63] Ingrid Zukerman,et al. A Generative Attentional Neural Network Model for Dialogue Act Classification , 2017, ACL.
[64] Andreas Stolcke,et al. Dialogue act modeling for automatic tagging and recognition of conversational speech , 2000, CL.
[65] Yoshua Bengio,et al. A Recurrent Latent Variable Model for Sequential Data , 2015, NIPS.
[66] Fredrik Olsson,et al. Active Learning for Dialogue Act Classification , 2011, INTERSPEECH.
[67] Rafael E. Banchs,et al. The Fourth Dialog State Tracking Challenge , 2016, IWSDS.
[68] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..