Results and Analysis
1) OHEM effectiveness evaluation : Four groups of experiments
have been designed under the same experimental conditions. Table 3
presents the experimental results. The introduction of OHEM has led to
an EER reduction in all models. In particular, the Resnet18- OHEM model
achieved a 42% reduction in EER, and the t-DCF index decreased by
nearly 50%. The best result for the single model is Res2net- OHEM,
achieving an EER of 2.13%. Fig. 1 compares the performance of Resnet18
and Resnet18-OHEM models for different logical attacks. As shown in
Fig.1, the Resnet18-OHEM system outperforms Resnet18 under most spoofing
attacks (A07-A15, A17). Moreover, after the introduction of OHEM, the
model has improved to different degrees for almost every attack
identification.
2) Fusion results and comparison with other systems : Table 4
shows our scores for fusing different models and compares them with
other models. After performing a two-by-two fusion of the models, it was
discovered that the S3 model combined with other models could provide
t-DCF values of 0.0233 and 0.0262, respectively. Analysis revealed that
the S3 model outperforms at identifying A17, and this benefit may be
fully realized by merging it with other models. Besides, EER=0.77 and
t-DCF=0.0228 were derived by combining the results of the S1, S2, and S3
models.
Table
3: The comparison between the four models after the introduction of
OHEM.