most citedExplaining Deep Learning Embeddings for Speech Emotion Recognition by Predicting Interpretable Acoustic Features

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.ET2026

Towards clinical adoption of voice and speech as measures of health: the need for harmonization

Nicholas Cummins, Vikram Ramanarayanan, Daniel Low +9

Speech and voice are multidimensional signals that capture both communicative intent and underlying physiological processes, providing a unique, non-invasive window into health. An…

cs.SD2024★ 1 cited

Explaining Deep Learning Embeddings for Speech Emotion Recognition by Predicting Interpretable Acoustic Features

Satvik Dixit, Daniel M. Low, Gasser Elbanna +2

Pre-trained deep learning embeddings have consistently shown superior performance over handcrafted acoustic features in speech emotion recognition (SER). However, unlike acoustic f…