An approach to continuous speech recognition based on layered self-adjusting decoding graph

In this paper, an approach of continuous speech recognition based on layered self-adjusting decoding graph is described. It utilizes a sca olding layer to support fast network expansion and releasing. A two level hashing structure is also described. It introduces self-adjusting capability in dynamic decoding on general re-entrant decoding network. In stack decoding, the sca olding layer in the proposed approach enables the decoder to look several layers into the future so that long span inter-word context dependency can be exactly preserved. Experimental results indicate that highly e cient decoding can be achieved with a signi cant savings on recognition resources.