In this paper, we propose a home video indexing using an audio information to detect an event both a rules-based method and a GMM-based method. Although exclusive audio segmentation and classification was usually used, various sounds overlap in practice, in which case an audio in which various sound overlapped is expressed by a labeling layered index. With the rules-based method, low-level audio features are used to determine indexes, which are classied such as speech, silence, music, and EVN(Environment Noise). The GMM-based method
which uses the same features as the rule based method also classifies an audio into the four classes. Smoothing is applied in order to determine the index. We show experiments in a few home video data.