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The paper presents an in-depth analysis of a less known interaction between Kneser-Ney smoothing and entropy pruning that leads to severe degradation in language model performance under aggressive pruning regimes. Experiments in a data-rich setup such as google.com voice search show a significant impact in WER as well: pruning Kneser-Ney and Katz models to 0.1 % of their original impacts speech recognition accuracy significantly, approx. 10 % relative. 1.
Chelba et al. (Sun,) studied this question.