Multistage utterance verification for keyword recognition-based online spoken content retrieval

This paper proposes a multistage utterance verification method as a post-processing technique for online spoken content retrieval in portable electric devices. The online spoken content retrieval system analyzes spoken content in an online manner and searches speech segments of pre-defined keywords. To maintain stable performance, we propose a reliable post-processing technique that verifies whether a found utterance or a candidate keyword segment can ultimately be categorized as a keyword. The proposed method involves a two-stage procedure for utterance verification. The first stage utilizes a confidence measure based on N-best log-likelihood recognition results. In the second stage, Dynamic Time Warping (DTW) algorithm is applied to obtain a verification result. As neither of these procedures requires high computational time and intensity, both are very suitable to online retrieval in portable devices such as smartphones. To assess the proposed technique, experiments on multimedia content retrieval tasks were performed using spoken broadcast news data. The evaluation results revealed that the performance of the proposed method was superior to that of the conventional approach.