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.