Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Ditthapron, Apiwat; O Agu, Emmanuel; C Lammert, Adam

Ditthapron, Apiwat; O Agu, Emmanuel; C Lammert, Adam.

Afiliación

Ditthapron A; Computer Science DepartmentWorcester Polytechnic Institute Worcester MA 01609 USA.
O Agu E; Computer Science DepartmentWorcester Polytechnic Institute Worcester MA 01609 USA.
C Lammert A; Biomedical Engineering DepartmentWorcester Polytechnic Institute Worcester MA 01609 USA.

IEEE Open J Eng Med Biol ; 2: 304-313, 2021.

Article en En | MEDLINE | ID: mdl-35402977

Palabras clave

Impact StatementThe proposed Deep-MASKS mitigates cross-talk in speech encoded as MFCC features, which are widely utilized to preserve voice privacy in passive health assessment and other speech applications on smartphones; Mel-Frequency Cepstrum Coefficients (MFCCs); overlapped speech; speaker representation; speech separation

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: IEEE Open J Eng Med Biol Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos

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