Beam Pruning Based on Quantile for Keyword Spotting

Abstract In this paper, we propose a novel pruning method for the Viterbi decoding in the task of keyword spotting. This method aims to reduce the computation time without any sacrifice of the detection performance. Firstly, α-quantile is employed to set the beam, and it reduces the hypothesis in proportion. Secondly, a flexible beam is achieved by a linear adjustment. The experiments conducted on the King-ASR-023 database show that the proposed method leads to a significant reduction in the computation time over the baseline system with fixed width of the beam.