Inserting a linear layer before a Transformer feed-forward layer during training and merging it at inference improves lightweight speech emotion recognition models with no added inference cost.
Enable deep learning on mobile devices: Methods, systems, and applications,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SD 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition
Inserting a linear layer before a Transformer feed-forward layer during training and merging it at inference improves lightweight speech emotion recognition models with no added inference cost.