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CONSEN: Complementary and Simultaneous Ensemble for Alzheimer's Disease Detection and MMSE Score Prediction

LONGBIN JIN (Konkuk University); Yealim Oh (Konkuk University); Hyunseo Kim (Konkuk University); Hyuntaek Jung (Konkuk University); Hyo Jin Jon (Konkuk University); Jung Eun Shin (Voinosis Inc.); Eun Yi Kim (Konkuk University)

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10 Jun 2023

This paper proposes a novel method for Alzheimer’s disease detection and MMSE prediction using a complementary and simultaneous ensemble (CONSEN) algorithm based on multilingual spontaneous speech. We define pause and intervention of speech to form disfluency features, as well as several acoustic features to train generalized models. With the help of the proposed CONSEN algorithm, our model achieves the best performance of 86.69% for AD detection and 3.727 RMSE for MMSE prediction, which is placed first rank in both tasks in ICASSP Signal Processing Grand Challenge: ADReSS-M Challenge 2023.

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  • SPS
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00
  • SPS
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00