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Efficient Viterbi Algorithms for Lexical Tree BasedModels

机译:基于词法树的模型的有效维特比算法

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In this paper we propose a family of Viterbi algorithms specialized for lexical tree based FSA and HMM acoustic models. Two algorithms to decode a tree lexicon with left-to-right models with or without skips and other algorithm which takes a directed acyclic graph as input and performs error correcting decoding are presented. They store the set of active states topologically sorted in contiguous memory queues. The number of basic operations needed to update each hypothesis is reduced and also more locality in memory is obtained reducing the expected number of cache misses and achieving a speed-up over other implementations.
机译:在本文中,我们提出了一系列Viterbi算法,专门用于基于词法树的FSA和HMM声学模型。提出了两种使用左右模型对树词典进行解码的算法(有或没有跳过),以及提出了将有向无环图作为输入并执行纠错解码的另一种算法。它们将拓扑排序的活动状态集存储在连续的内存队列中。减少了更新每个假设所需的基本操作的数量,并且还获得了更多的内存局部性,从而减少了预期的高速缓存未命中数,并实现了与其他实现方式相比的提速。

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