A Multi-Modal Feature Embedding Approach to Diagnose Alzheimer Disease from Spoken Language
Table 3: N-gram Model Evaluation
['[BOLD] N-gram', '[BOLD] Smoothing Method', '[BOLD] Accuracy', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1-Score']
As discussed before of all, we performed each of the techniques separately and evaluated them on the data, then we use combinations of them to reach a better accuracy. First model to evaluate was N-gram model. In this work we used 2, 3 and 4-gram model with both Good-Turing and Kneser-Ney smoothing methods.