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This paper focuses on discriminative n-gram language models for large vocabulary speech recognition. We have proposed a novel training method called the round-robin duel discrimination (R2D2) method. Our previous report showed that R2D2 outperforms conventional methods on word n-gram based discriminative language models (DLMs). In this paper, we achieve additional error reduction and one-pass decoding...
This paper proposes a novel one-pass search algorithm with on-the-fly composition of weighted finite-state transducers (WFSTs) for large-vocabulary continuous-speech recognition. In the standard search method with on-the-fly composition, two or more WFSTs are composed during decoding, and a Viterbi search is performed based on the composed search space. With this new method, a Viterbi search is performed...
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