In Defence of Metric Learning for Speaker Recognition
In Defence of Metric Learning for Speaker Recognition
The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level representation that has small intra-speaker and large inter-speaker distance.A popular belief in speaker recognition is that networks trained with classification objectives outperform metric learning methods.In …