Lattice-Based Unsupervised Test-Time Adaptationof Neural Network Acoustic Models
Table 4: WER for adaptation of the MGB model to episodes in the longitudinal eval data.
['[EMPTY]', 'eval']
This provides more adaptation data ( 30-45 minutes per episode), but perhaps at the cost of losing finer granularity for adaptation. Using the best path with all parameters yields almost no gains (∼1%). When only adapting a subset of the parameters with LHUC the results are more stable, but does not perform as well as all parameters with lattice supervision.