A matching algorithm between arbitrary sections of two speech data sets for speech retrieval

This paper proposes a new matching algorithm to retrieve speech information from a speech database by speech query that allows continuous input. The algorithm is called Shift Continuous DP (CDP). Shift CDP extracts similar sections between two speech data sets. Two speech data sets are considered as reference patterns that are regarded as a speech database and input speech respectively. Shift CDP applies CDP to a constant length of unit reference patterns and provides a fast match between arbitrary sections in the reference pattern and the input speech. The algorithm allows endless input and real-time responses for the input speech query. Experiments were conducted for conversational speech and the results showed Shift CDP was successful in detecting similar sections between arbitrary sections of the reference speech and arbitrary sections of the input speech. This method can be applied to all kinds of time sequence data such as moving images.