Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech
Table 5: ABX scores on the ZeroSpeech 19 English test set using features derived from the output of the Res3 block of the ResDAVEnet audio branch (pre-quantization).
['Model ID', 'Res3 ABX']
We present results from two experiments that support this view. We observe that the ABX error rate changes very little within each individual curriculum. This indicates that the initial model sets the stage for which layer learns to capture phonetic information with the highest salience, and that subsequent training steps do not tend to move this information elsewhere.