Finding Difficult Speakers in Automatic Speaker Recognition

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VoxCeleb: A Large-Scale Speaker Identification Dataset (2017, background): “…and intrinsic variations; extrinsic variations include background chatter and music, laughter, reverberation, channel and micro-phone effects; while intrinsic variations are factors inherent to the speaker themself such as age, accent, emotion, intonation and manner of speaking, amongst others [1].”
CN-Celeb: A Challenging Chinese Speaker Recognition Dataset (2019, background): “These uncertainties make the speaker recognition task highly challenging [1, 2].”
Voxceleb: Large-scale speaker verification in the wild (2020, background): “…variations; extrinsic variations include background chatter and music, laughter, reverberation, channel and microphone effects; while intrinsic variations are factors inherent to the speakers themselves such as age, accent, emotion, intonation and manner of speaking, amongst others (Stoll, 2011).”