Deep Speaker Embeddings for Far-Field Speaker Recognition on Short Utterances
Table 3: The results of the publicly available model from [12] and the proposed ResNet34-MFB80-AM-TrainData-IV on the short utterances protocol (generated from VoxCeleb1).
['Embedding extractor', 'EER, % (1s)', 'EER, % (2s)', 'EER, % (5s)']
A comparison protocol was generated by randomly sampling 100 target and 100 imposter pairs for each speaker from a total of 1,251 speakers in VoxCeleb1, resulting in 250,048 unique comparisons. The observed differences can be attributed to the differences in test protocols. Nevertheless, synchronous testing showed significantly better quality of the proposed model for various short durations (1 sec, 2 sec and 5 sec).