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--- title: "Mahajan 2021" type: concept related: [Shah 2021] source: https://www.jemoka.com/posts/kbhmahajan_2021/ confidence: high status: active --- DOI: 10.3389/fnagi.2021.623607 One-Liner Trained a bimodal model on speech/text with GRU on speech and CNN-LSTM on text. Novelty A post-2019 NLP paper that doesn’t use transformers! (so faster (they used CNN-LSTM) lighter easier) “Our work sheds light on why the accuracy of these models drops to 72.92% on the ADReSS dataset, whereas, they gave state of the art results on the DementiaBank dataset.” Notable Methods Bi-Modal audio and transcript processing vis a vi Shah 2021, but with a CNN-LSTM and GRU on the other side. Key Figs Figure 1: Proposed Architecture The figure highlights the authors’ proposed architecture Figure 2: confusion matrix In addition to validating prior work by Karlekar 2018 and Di Palo 2019, proposed model C and got accuracy of \(73.92\%\).