Guiding CTC Posterior Spike Timingsfor Improved Posterior Fusion and Knowledge Distillation
Table 1: WERs for posterior fusion and ROVER of UniLSTM phone CTC models. [%]
['[EMPTY]', 'SWB', 'CH']
We trained 4 UniLSTM models with the standard training. In 1A, we averaged the Word Error Rates (WERs) for the 4 decoding outputs from the 4 models. For posterior fusion in 1B, we averaged the posteriors from the 4 models and used it for decoding with the graph. ROVER gave us a solid improvement in 1C.