Speaker Adaptation for End-to-End CTC Models
Table 9: WERs (%) for supervised and unsupervised MTL adaptations for the mix-unit CTC model on the 7-speaker set.
['Adapt. type', '# of utt.', '[ITALIC] β=1', '[ITALIC] β=0.8', '[ITALIC] β=0.5', '[ITALIC] β=0.2']
, we report the results of supervised and unsupervised MTL adaptations for the mix-unit CTC model on the 7-speaker dataset. For the supervised MTL adaptation, the best WERs are 16.60%, 15.88%, and 14.96% for adapting with 10, 50, 200 utterances, respectively. The corresponding relative WERRs are 0.97%, 5.25%, and 10.75% over the baseline SI model. For the unsupervised MTL adaptation, we observe best WERs as 16.53%, 15.92%, and 15.63% with 10, 50, 200 adaptation utterances, respectively. The corresponding relative WERRs are 1.37%, 5.04%, and 6.79% over the baseline SI model. Both the best relative WERRs for supervised and unsupervised scenarios by MTL adaptations are larger than the best WERRs by KLD adaptations. This indicate MTL adaptation is more effective than KLD adaptation for the mix-unit CTC model.