Using character-duration sequences from WhisperX, a transformer identifies speakers with balanced accuracy of 0.39 on LibriSpeech but only 0.03 on VoxCeleb1, and fusion with x-vectors does not improve accuracy.
Additionally, it is better suited to our closed-set identi- fication task than other commonly used measures, such as equal error rate (EER)
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Rhythm Features for Speaker Identification
Using character-duration sequences from WhisperX, a transformer identifies speakers with balanced accuracy of 0.39 on LibriSpeech but only 0.03 on VoxCeleb1, and fusion with x-vectors does not improve accuracy.