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Table 3 Testing speed comparisons of UP-NNLMs and NNLMs for different hidden layers

From: Empirically combining unnormalized NNLM and back-off N-gram for fast N-best rescoring in speech recognition

Model Speed × 103 (words/second)
  10 50 100 200 300 400
RNNLMa 0.78 0.23 0.11 0.056 0.041 0.029
+Class layer 70.87 28.5 13.94 7.39 4.21 3.10
UP-RNNLM 400.01 197.75 80.30 26.93 11.95 7.20
FNNLMa 2.72 1.63 0.35 0.291 0.214 0.14
+Class layer 124.89 66.83 36.02 16.16 9.55 5.75
UP-FNNLM 678.48 209.16 83.95 25.33 17.77 11.63
fast-UP-FNNLM 746.43 557.18 406.47 291.35 240.38 201.75
  1. aThe implementations of RNNLM and FNNLM are based on the open source toolkits, CSLM and RNNLM. The matrix and vector operations in CSLM toolkit are optimized via MKL Library, so that the evaluation of FNNLM is faster than RNNLM with the same size of hidden layer.