Syllable-based relevance feedback techniques for Mandarin voice record retrieval using speech queries

In order to solve the problem with the new environment of fast growth of audio resources on the Internet, we have presented a syllable-based approach which is capable of retrieving Mandarin voice records using queries of unconstrained speech. However, the performance achieved by this previously proposed approach is still not satisfactory, and one of the reason is that very often the information provided by the speech query for the request subject may not be sufficient. We present approaches based the relevance feedback technique to improving the performance of the previous research. The proposed approaches include a relevance measure adjustment scheme using a relevance table for the voice database, a query expansion scheme to generate a new query including the feedback information, and a combination of these two schemes. Extensive preliminary experiments were performed and demonstrated.