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CORR
2004
Springer

Effects of Language Modeling on Speech-driven Question Answering

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Effects of Language Modeling on Speech-driven Question Answering
We integrate automatic speech recognition (ASR) and question answering (QA) to realize a speech-driven QA system, and evaluate its performance. We adapt an Ngram 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.
Tomoyosi Akiba, Atsushi Fujii, Katunobu Itou
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2004
Where CORR
Authors Tomoyosi Akiba, Atsushi Fujii, Katunobu Itou
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