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This paper is concerned with the task of speaker verification on audio withmultiple overlapping speakers. Most speaker verification systems are designedwith the assumption of a single speaker being present in a given audio segment.However, in a real-world setting this assumption does not always hold. In thispaper, we demonstrate that current speaker verification systems are not robustagainst audio with noticeable speaker overlap. To alleviate this issue, wepropose margin-mixup, a simple training strategy that can easily be adopted byexisting speaker verification pipelines to make the resulting speakerembeddings robust against multi-speaker audio. In contrast to other methods,margin-mixup requires no alterations to regular speaker verificationarchitectures, while attaining better results. On our multi-speaker test setbased on VoxCeleb1, the proposed margin-mixup strategy improves the EER onaverage with 44.4% relative to our state-of-the-art speaker verificationbaseline systems.

Margin-Mixup: A Method for Robust Speaker Verification in Multi-Speaker Audio