EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Extracting the names of genes and gene products with a hidden Markov model
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Message Understanding Conference-6: a brief history
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Hierarchical Clustering Algorithms for Document Datasets
Data Mining and Knowledge Discovery
The Penn Chinese TreeBank: Phrase structure annotation of a large corpus
Natural Language Engineering
Improving information extraction by modeling errors in speech recognizer output
HLT '01 Proceedings of the first international conference on Human language technology research
Efficient support vector classifiers for named entity recognition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Information extraction from voicemail
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Named entity recognition using an HMM-based chunk tagger
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Chunking with support vector machines
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Introduction to the CoNLL-2002 shared task: language-independent named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Maximum entropy models for named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Named entity recognition with a maximum entropy approach
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Spoken document retrieval from call-center conversations
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Multi-criteria-based active learning for named entity recognition
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Extracting personal names from email: applying named entity recognition to informal text
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Robust named entity extraction from large spoken archives
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Effects of word confusion networks on voice search
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Using N-best lists for named entity recognition from Chinese speech
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Performance prediction for exponential language models
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Shrinking exponential language models
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Domain adaptation of rule-based annotators for named-entity recognition tasks
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Advances in speech transcription at IBM under the DARPA EARS program
IEEE Transactions on Audio, Speech, and Language Processing
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Named Entity (NE) detection from Conversational Telephone Speech (CTS) is important from business aspects. However, results of Automatic Speech Recognition (ASR) inevitably contain errors and this makes NE detection from CTS more difficult than from written text. One of the options to detect NEs is to use a statistical NE model. In order to capture the nature of ASR errors, the NE model is usually trained with the ASR one-best results instead of manually transcribed text and then is applied to the ASR one-best results of speech that contain NEs. To make NE detection more robust to ASR errors, we propose using Word Confusion Networks (WCNs), sequences of bundled words, for both NE modeling and detection by regarding the word bundles as units instead of the independent words. We realize this by clustering similar word bundles that may originate from the same word. We trained the NE models that predict the NE tag sequences from the sequence of the word bundles with the maximum entropy principle. Note that clustering of word bundles is conducted in advance of NE modeling and thus our proposed method can combine with any NE modeling method. We conducted experiments using real-life call-center data. The experimental results showed that by using the WCNs, the accuracy of NE detection improved regardless of the NE modeling method.