## 2 Experimental Methodology
### Train-Test Dataset and Result Evaluation Metric  
The ADReSSo-2021 dataset [25] has subjects from the healthy control group (CN cohort) and subjects with cognitive decline (assigned to the AD cohort). Of the 237 audio recordings made available, which were balanced for age and gender (to avoid biases), 166 were used for training, and the models were tested against a mutually exclusive 71 audio recordings. The number of audio recordings in the AD training and testing group were 87 and 35, respectively. The CN training and testing group contained 79 and 36 recordings, respectively.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Resolution (Modality)** & **Feature** & \begin{tabular}{c} **Models** \\ **(Number of Estimators, If Applicable)** \\ \end{tabular} \\ \hline \multirow{6}{*}{file-level (Audio)} & eGeMAPS & Bagging Classifier (500) \\  & Emobase-Large & Hard Voting \\  & & (Random Forest (1000) + Bagging \\  & & Classifier (200)) \\  & Emobase & Bagging Classifier (200) \\  & Speech/Silence * & Catboost (1000) \\  & Energy–Time plot & CNN \\ \hline \multirow{6}{*}{file-level (Text)} & \begin{tabular}{c} Key of Text Analytics \\ Key of Text Analytics-Extended \\ Summed Word Embedding \\ \end{tabular} & \begin{tabular}{c} (500) \\ Hand Voting \\ Hard Voting \\ (Random Forest (500) + Gradient \\ Boosting (500) + Bagging Classifier (500)) \\ DNN (4-layers) \\ DNN (5-layers) \\ DNN (3-layers) \\ DNN (3-layers) \\ \end{tabular} \\  & \
\begin{tabular}{c} OpenSMILE (Prosody) \\ VGG \\ OpenL3 \\ \end{tabular} &
\begin{tabular}{c} GMM-UBM \\ BiLSTM \\ BiLSTM \\ BiLSTM \\ \end{tabular} \\ \hline frame-level (Text) & Word Embedding & BiLSTM \\ \hline \hline \end{tabular}  
* See Appendix A for details of model architecture.  
\end{table}
Table 2: Training features and models investigated in this work are shown. AD: Alzheimer’s Dementia; CN: Cognitively Normal.  
The results for AD classification task are shown in terms of accuracy (see Equation (2)). We considered the AD class to be the positive one.  
\[Accuracy=\frac{True\ Positive+True\ Negative}{True\ Positive+True\ Negative+False\ Positive+False\ Negative} \tag{2}\]  
The ADReSSo-2021 dataset [25] is a subset of the English Pitt corpus of DementiaBank [26; 27], where AD and CN subjects respond to the Cookie Theft stimulus from the Boston Diagnostic Aphasia Examination [45] consisting of the following: average age of AD patients is \(69.3\pm 6.9\) years; average age of CN subjects is \(66.0\pm 6.3\) years. A total of 237 audio recordings of the Cookie Theft picture description task is provided, constituting of 122 CN subjects (43 men, 79 women) and 115 patients with AD diagnosis (40 men, 75 women). These recordings also include the interviewer's instructions to the subjects or occasional short prompts. The average duration of interviews of AD and CN groups was \(65.7\pm 38.6\) and \(61.6\pm 26.9\) seconds, respectively. To minimize biases, not only was this dataset matched for age and gender, but also carefully matched to avoid commonly overlooked issues, such as repeated occurrences of speech from the same participant, variations in audio quality, etc. The audio was acoustically enhanced by removing stationary noise, and audio volume normalization to control for recording condition variations, such as microphone placement, was also performed [25].