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Test implementation using a toy dataset suggests it is an option, but two new problems come to mind:
in picking from the most common sub-sequences that the used BPE implementation returns.
This is fairly easy to solve by ensuring the replacement function starts doing so with the sub-sequence with highest number of occurrences, then goes to the second most common until there is no frames left that match any sub-sequence in the vocabulary.
When tested with real world data, it would often be the case that there is no repeating label sub-sequences. This suggests a bigger problem within the pipeline, likely spread across all three stages of segmentation/analysis/classification and is unlikely to be resolved at this point.
It could help a lot to detect commonly occuring sub-sequences and replace them with a single token.
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