@inproceedings{f7779155001945a7ab1fa20b48217ce4,
title = "Anchored speech recognition for question answering",
abstract = "In this paper, we propose a novel question answering system that searches for responses from spoken documents such as broadcast news stories and conversations. We propose a novel two-step approach, which we refer to as anchored speech recognition, to improve the speech recognition of the sentence that supports the answer. In the first step, the sentence that is highly likely to contain the answer is retrieved among the spoken data that has been transcribed using a generic automatic speech recognition (ASR) system. This candidate sentence is then re-recognized in the second step by constraining the ASR search space using the lexical information in the question. Our analysis showed that ASR errors caused a 35\% degradation in the performance of the question answering system. Experiments with the proposed anchored recognition approach indicated a significant improvement in the performance of the question answering module, recovering 30\% of the answers erroneous due to ASR.",
author = "Sibel Yaman and Gokhan Tur and Dimitra Vergyri and Dilek Hakkani-Tur and Mary Harper and Wen Wang",
note = "Acknowledgments: This work was funded by DARPA under contract No. HR0011-06-C-0023. Any conclusions or recommendations are those of the authors and do not necessarily reflect the views of DARPA.; 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009 ; Conference date: 31-05-2009 Through 05-06-2009",
year = "2009",
language = "English (US)",
series = "NAACL-HLT 2009 - Human Language Technologies: 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers",
publisher = "Association for Computational Linguistics (ACL)",
pages = "265--268",
editor = "Mari Ostendorf and Michael Collins and Shri Narayanan and Oard, \{Douglas W.\} and Lucy Vanderwende",
booktitle = "NAACL-HLT 2009 - Human Language Technologies",
address = "United States",
}