Robust tree-structured named entities recognition from speech

Christian Raymond 1
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Named Entity Recognition (NER) is a well-known Natural Language Processing (NLP) task, used as a preliminary processing to provide a semantic level to more complex tasks. Recently a new set of named entities has been defined, this set has a multilevel tree structure, where base entities are combined to define more complex ones. In this paper I describe, an effective and original NER system robust to noisy speech inputs that ranked first at the 2012 ETAP NER evaluation campaign with results far better than those of the other participating systems.
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Conference papers
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Submitted on : Tuesday, June 4, 2013 - 2:56:20 PM
Last modification on : Friday, November 16, 2018 - 1:23:08 AM
Long-term archiving on : Thursday, September 5, 2013 - 4:22:37 AM



  • HAL Id : hal-00830142, version 1


Christian Raymond. Robust tree-structured named entities recognition from speech. Proceedings of the International Conference on Acoustic Speech and Signal Processing, May 2013, Vancouver, Canada. ⟨hal-00830142⟩



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