A wave decoder for continuous speech recognition

A wave decoder based on the general re-entrant network for continuous speech recognition is described. The decoder design is based on the concept of self adjusting decoding graph in which the decoding network is expanded and released frame synchronously. The fast network expansion and release are made possible by utilizing a novel dynamic network scaffolding layer. The self adjusting decoding graph is obtained by slicing the traditional decoding network horizontally for separation of different knowledge sources and vertically according to each time instant in search. A two layer hashing structure and an admissible arc predication scheme are described. These methods significantly reduce the arc mortality rate, a problem which plagues the efficiency of the dynamic decoder. Experimental results demonstrate that an order of magnitude reduction of decoding resources can be achieved based on the proposed approach