most citedUncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification

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eess.AS2023★ 1 cited

Uncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification

Simon W. McKnight, Aidan O. T. Hogg, Vincent W. Neo +1

This paper studies modulation spectrum features () and mel-frequency cepstral coefficients () in joint speaker diarization and identification (JSID). JSID is important as spe…