Deep Speaker Embeddings for Far-Field Speaker Recognition on Short Utterances
Table 4: Results of the investigated systems for VOiCES (eval set), VOiCES (dev set) and VoxCeleb1-O (cleaned) protocols in relation to different length of test waveform.
['Embedding extractor', 'VOiCES (eval set) EER, % (1s/2s/5s/full)', 'VOiCES (dev set) EER, % (1s/2s/5s/full)', 'VoxCeleb1-O (cleaned) EER, % (1s/2s/5s/full)']
In order to simplify the experiments and improve the reproducibility of our results, we did not use normalization and U-net based VAD for these tests. This is confirmed by the results of ResNet34-MFB80-AM-TrainData-I model, trained on 1-second and 2-second segments. Thus, it is possible to slightly improve the quality of the systems for short durations in this way.