Minimum error classification of keyword-sequences

A novel spotter design method, i.e., minimum error classification of keyword-sequences (MECK), is proposed. In contrast with conventional approaches, the proposed method directly aims at reducing errors of classifying keyword-sequences (strings of prescribed keyword categories) through a mathematically proven, GPD-based optimization process. Experiments in Japanese keyword spotting tasks clearly demonstrate the utility of a MECK-trained, prototype-based spotter