Open-domain name error detection using a multi-task RNN

Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Volumn , Issue , 2015, Pages 737-746

  Cheng, Hao ^a   Fang, Hao ^a   Ostendorf, Mari ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; RECURRENT NEURAL NETWORKS; SPEECH RECOGNITION;

AUTOMATIC DETECTION; DOMAIN NAMES; LANGUAGE PROCESSING; LEXICAL FEATURES; N-GRAMS; OUT OF VOCABULARY WORDS; SENTENCE LEVEL; TEXT DATA;

ERROR DETECTION;

EID: 84959917665     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/d15-1085     Document Type: Conference Paper

References (29)

1. N. F. Ayan, A. Mandal, M. Frandsen, Jing Zheng, P. Blasco, A. Kathol, F. Bechet, B. Favre, A. Marin, T. Kwiatkowski, M. Ostendorf, L. Zettlemoyer, P. Salletmayr, J. Hirschberg, and S. Stoyanchev. 2013. "Can you give me another word for hyperbaric?" Improving speech translation using targeted clarification questions. In Proc. ICASSP, pages 8391-8395.
2. Rich Caruana. 1997. Multitask learning. Machine Learning, 28, July.
3. Wei Chen, Sankaranarayanan Ananthakrishnan, Rohit Prasad, and Prem Natarajan. 2013. Variable-span out-of-vocabulary named entity detection. In Proc. Interspeech, pages 3761-3765.
4. Ronan Collobert and Jason Weston. 2008. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proc. ICML.
5. John Duchi, Elad Hazan, and Yoram Singer. 2011. Adaptive subgradient methods for online learning and stochastic optimization. Machine Learning Research, 12.
6. Jenny Rose Finkel, Trond Grenager, and Christopher Manning. 2005. Incorporating non-local information into information extraction systems by gibbs sampling. In Proc. ACL.
7. Ji He, Alex Marin, and Mari Ostendorf. 2014. Effective data-driven feature learning for detecting name errors in automatic speech recognition. In Proc. SLT.
8. Christopher Manning Jeffery Pennington, Richard Socher. 2014. Glove: Global vectors for word representations. In Proc. EMNLP.
9. Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014. A convolutional neural network for modelling sentences. In Proc. ACL.
10. Yoon Kim. 2014. Convolutional neural networks for sentence classification. In Proc. EMNLP.
11. Siwei Lai, Liheng Xu, Kang Liu, and Jun. Zhao. 2015. Recurrent convolutional neural networks for text classification. In Proc. AAAI.
12. Xiaodong Liu, Jianfeng Gao, Xiaodong He, Li Deng, Kevin Duh, and Ye-Yi Wang. 2015. Representation learning using multi-task deep neural networks for semantic classification and information retrieval. In Proc. NAACL.
13. Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014. The Stanford CoreNLP natural language processing toolkit. In Proc. ACL.
14. Alex Marin, Mari Ostendorf, and Ji He. 2015. Learning phrase patterns for asr error detection using semantic similarity. In Proc. Interspeech.
15. Alex Marin. 2015. Effective use of cross-domain parsing in automatic speech recognition and error detection. Ph. D. thesis, University of Washington.
16. Tomas Mikolov, Martin Karafiat, Lukas Burget, Jan Cernocky, and Sanjeev Khudanpur. 2010. Recurrent neural network based language model. In Proc. Interspeech.
17. T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. 2013a. Distributed representations of words and phrases and their compositionality. In Proc. NIPS.
18. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013b. Distributed representations of words and phrases and their compositionality. In Proc. NIPS.
19. Tomas Mikolov, Wen Tau Yih, and Geoffrey Zweig. 2013c. Linguistic regularities in continuous space word representations. In Proc. NAACL-HLT.
20. Andriy Mnih and Yee Whye Teh. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proc. ICML.
21. David Palmer and Mari Ostendorf. 2005. Improving out-of-vocabulary name resolution. Computer Speech and language, 19(1):107-128.
22. Carolina Parada, Mark Dredze, and Frederick Jelinek. 2011. OOV sensitive named-entity recognition in speech. In Proc. Interspeech, pages 2085-2088.
23. Michael L. Seltzer and Jasha Droppo. 2013. Multitask learning in deep neural networks for improved phoneme recognition. In Proc. ICASSP.
24. Richard Socher, Brody Huval, Christopher D. Manning, and Andrew Y. Ng. 2012. Semantic compositionality through recursive matrix-vector space. In Proc. EMNLP-CoNLL.
25. Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proc. EMNLP.
26. Katsuhito Sudoh, Hajime Tsukada, and Hideki Isozaki. 2006. Incorporating speech recognition confidence into discriminative named entity recognition of speech. In Proc. ACL.
27. Kai Sheng Tai, Richard Socher, and Christopher D. Manning. 2015. Improved semantic representations from tree-structured long short-term memory networks. In Proc. ACL.
28. Laurens Van Der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Machine Learning Research, 9, November.
29. Zhizheng Wu, Cassia Valentini-Botinhao, Oliver Watts, and Simon King. 2015. Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis. In Proc. ICASSP.