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Effects of Language Modeling on Speech-driven Question Answering

Tomoyosi Akiba·Atsushi Fujii·Katunobu Itou
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Abstract

We integrate automatic speech recognition (ASR) and question answering (QA) to realize a speech-driven QA system, and evaluate its performance. We adapt an N-gram language model to natural language questions, so that the input of our system can be recognized with a high accuracy. We target WH-questions which consist of the topic part and fixed phrase used to ask about something. We first produce a general N-gram model intended to recognize the topic and emphasize the counts of the N-grams that correspond to the fixed phrases. Given a transcription by the ASR engine, the QA engine extracts the answer candidates from target documents. We propose a passage retrieval method robust against recognition errors in the transcription. We use the QA test collection produced in NTCIR, which is a TREC-style evaluation workshop, and show the effectiveness of our method by means of experiments.

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Tomoyosi Akiba, Atsushi Fujii, Katunobu Itou. 2004-07-10. Effects of Language Modeling on Speech-driven Question Answering. https://arxiv.org/abs/cs/0407028

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