Considering context around source features about knn-vc HOT 2 CLOSED

Hi @wilson97, we also thought that additional context would be useful and tried two different methods to incorporate information from neighboring features. The first method we tried was similar to your proposal, where we used a weighted sum of the distances between triplets of frames. For the second method we adapted the dynamic programming algorithm for unit selection (from concatenative synthesis) where you encourage smoothness between the selected frames. Unfortunately, neither of them were significantly different from the naive kNN approach, so we went with that for simplicity.

However, there is definitely room for experimentation! I think incorporating smoothness constraints or neighboring context could help get rid of some of the boundary artefacts we sometimes get. Let me know if you find something that works well.

Hope that helps!

from knn-vc.

The classic was of incorporating trajectory in HMM/GMM models was to use deltas and delta-deltas, typically only from the previous frame. That might be another approach worth tinkering with

from knn-vc.