Multimodal Domain Generalization for Depression Detection: An Attention-Based BiLSTM Network with Domain-Adversarial Training
Depression detection models tend to pick up who is speaking, not whether they are depressed.
Depression detection models tend to pick up who is speaking, not whether they are depressed.
A survey of composer-identification research with a simple point: before trusting a result, check whether the evaluation is strong enough to support it.
A speech-emotion classifier looks fine on clean audio, then falls apart under small adversarial tweaks.
A benchmark study of symbolic-music feature extraction showing where MIDI still holds up, where richer notation helps, and why harmony features can shift the result.
A study on what gets lost when a performance is reduced to MIDI, and on how to evaluate resynthesis in a way that follows what listeners actually hear.