  Speaker recognition on household devices, such as smart speakers, features
several challenges: (i) robustness across a vast number of heterogeneous
domains (households), (ii) short utterances, (iii) possibly absent speaker
labels of the enrollment data (passive enrollment), and (iv) presence of
unknown persons (guests). While many commercial products exist, there is less
published research and no publicly-available evaluation protocols or
open-source baselines. Our work serves to bridge this gap by providing an
accessible evaluation benchmark derived from public resources (VoxCeleb and
ASVspoof 2019 data) along with a preliminary pool of open-source baselines.
This includes four algorithms for active enrollment (speaker labels available)
and one algorithm for passive enrollment.
