An Attentional Neural Network Architecture for Folk Song Classification
Table 2: Binary classification precision scores for each model.
['Model Comparison Repres. type', 'Model Comparison mw size', 'Model Comparison Model', 'Model Comparison Precision']
We compare the classification results for intervallic, and rhythmical representations of the songs using the proposed architecture with the two base models. The attention network outperforms both baselines in all types of representations and for mw of size 2 and 3. Smaller interval motifs seem to be the best representation in terms of classification precision. We should note the good quality of the results in general not only for the proposed archtecture, but also for the doc2vec model, which highlights the quality of the motif representation and its impact on classification accuracy.