An STD System for OOV Query Terms Integrating Multiple STD Results of Various Subword units

We have been proposing a Spoken Term Detection (STD) method for Out-Of-Vocabulary (OOV) query terms integrating various subword recognition results using monophone, triphone, demiphone, one third phone, and Sub-phonetic segment (SPS) models. In the proposed method, subword-based ASR (Automatic Speech Recognition) is performed for all spoken documents and subword recognition results are generated using subword acoustic models and subword language models. When a query term is given, the subword sequence of the query term is searched for all subword sequences of subword recognition results of spoken documents. Here, we use acoustical distances between subwords when matching the two subword sequences by Continuous Dynamic Programming. We have also proposed the method rescoring and integrating multiple STD results obtained using various subword units. Each candidate segment has a distance, the segment number and the document number. Re-scoring is performed using distances each of high ranked candidate segments, and the last distance is obtained by integrating then linearly using weighting factors. In STD tasks (SDPWS) of IR for Spoken Documents in NTCIR-10, we apply various subword models to the STD tasks and integrate multiple STD results obtained from these subword models.