Inactive-node detection and memory optimization in WFST decoder lattice generation algorithm

doi:10.7523/j.issn.2095-6134.2019.01.015

Abstract

Abstract: Decoder is the core module of speech recognition system, and the decoder based on the weighted finite-state transducers (WFST) is a typical form of decoder. We analyze the resource occupation of WFST-based static decoder in practice, and propose a strategy for dynamical recovery of system resources by detecting inactive nodes during decoding and lattice generation. Finally, we carry out experiments on the OpenKWS 15 dataset to show that the decoder with this strategy consumes about 75% less memory than decoders that do not reclaim system resources.

Key words: speech recognition decoder, WFST, engineering application, memory recycling

CLC Number:

TN912

DING Jiawei, LIU Jia, ZHANG Weiqiang, FENG Yunbo, LIU Lijun, YU Le. Inactive-node detection and memory optimization in WFST decoder lattice generation algorithm[J]. , 2019, 36(1): 109-114.

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