Deep Speaker Verification: Do We Need End to End?
Table 2: EER(%) results of the three SV systems.
['Systems', 'Scoring', 'EER% C(4-4)', 'EER% C(40-4)']
Firstly we compare the three SV systems with their own best configurations, say, i-vector + PLDA, deep feature + LDA. It can be seen that the deep feature system performs the best, and the end-to-end system is inferior compared to the other two systems. The inferior performance of the end-to-end system compared to the i-vector system with limited training data is also consistent with the results reported by Snyder et al. when the training set contained 5,000 speakers.