End-to-End Neural Diarization:Reformulating Speaker Diarization asSimple Multi-label Classification
TABLE VI: DERs (%) for different numbers of encoder blocks and warm-up steps with/without residual connections. The models were trained with SimBeta2
['Enc. blocks', 'Warm. steps', 'Res. con.', 'Simulated  [ITALIC] β=2', 'Simulated  [ITALIC] β=3', 'Simulated  [ITALIC] β=5', 'Real CH', 'Real CSJ']
As noted in Sec. In this section, we examined deeper model configurations using more encoder blocks with residual connections. The loss curves for different numbers of encoder blocks and warm-up steps are shown in Fig. The models with four encoder blocks reduced the validation loss compared with the one with two encoder blocks. Moreover, the validation loss was reduced by increasing the number of warm-up steps from 25,000 to 100,000. The results show that increasing the number of encoder blocks significantly improved performance.