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The aim of this research is a human-oriented spoken dialog system which provides replies to a variety of users' utterances. The example-based response generation method searches a question and answer database (QADB) for the example question most similar to a user utterance. With this method, the system can answer a question difficult for a model to express. A QADB is constructed from question and answer pairs (QA pairs) by employing a large corpus. In order to enhance robustness to recognition errors of inarticulate utterances such as children utterances, we propose to use speech recognition results, instead of manual transcriptions, as example questions. We also introduce an optimization method that removes inappropriate QA pairs from a QADB to maximize response accuracy. We show that our method improves the response accuracy of utterances especially for children utterances in the open test.