Yaman, S., Tür, G., Vergyri, D., Hakkani-Tur, D., Harper, M., & Wang, W. (2009, June). Anchored Speech Recognition for Question Answering. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (pp. 265-268).
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.