Table 6 100-Best rescoring with different LMs on Hub5’00-SWB and RT03S-FSH
From: RNN language model with word clustering and class-based output layer
Model | Perplexity | WER (%, absolute change) | ||
|---|---|---|---|---|
Hub5’00-SWB | RT03S-FSH | Hub5’00-SWB | RT03S-FSH | |
LM-KN3 | 89.40 | 66.76 | 24.5 | 27.5 |
LM-KN5 | 86.78 | 63.80 | 24.1 (−0.4) | 27.1 (−0.4) |
RNNLM-Freq | 72.47 | 55.76 | 22.9 (−1.6) | 25.9 (−1.6) |
RNNLM-Freq + LM-KN5 | 67.66 | 52.15 | 22.4 (−2.1) | 25.5 (−2.0) |
RNNLM-Brown | 69.91 | 54.48 | 22.6 (−1.9) | 25.7 (−1.8) |
RNNLM-Brown + LM-KN5 | 66.00 | 51.24 | 22.2 (−2.3) | 25.3 (−2.2) |