An efficient mechanism for searching Arabic audio libraries

In this paper we propose an approach that allows the user to query an Arabic audio library using voice. We use a combination of class-based language models and robust interpretation to recognize and identify the spoken keywords. The mechanism uses a large vocabulary recognition system (LVCSR) to implement the functionality of an Arabic authority control system. A series of experiments were performed to assess the accuracy and the robustness of the proposed approach: restricted grammar recognition with semantic interpretation, class-based statistical language models (CB-SLM) with robust interpretation, and generalized CB-SLM. The results have shown that the combination of CB-SLM and robust interpretation provides better accuracy and robustness than the traditional grammar-based parsing.