Audio Feature Interpretability

What I worked on

Investigated how to reconstruct or interpret the 768-dim latent features from wav2vec.

What I noticed

• There’s no direct inverse transformation.
• Suggested approaches: train a decoder, use synthesis models, or build an autoencoder for feature inversion.
• Visualization or correlation with known features (pitch, phonemes) could provide interpretive clues.

”Aha” Moment

n/a

What still feels messy

The mechanics of mapping latent vectors back to meaningful audio or interpretable units.

Next step

Train a lightweight decoder or experiment with feature visualization methods.