Question 1

What problem does GAN-AraEmo address in Arabic speech emotion recognition?

Accepted Answer

It targets the lack of annotated emotional speech data and the linguistic complexity introduced by diverse Arabic dialects, which reduces model robustness and generalization.

Question 2

How is GAN-AraEmo designed to generate high-quality synthetic emotional speech?

Accepted Answer

It uses a multi-scale generator with attention mechanisms and an enhanced discriminator with spectral normalization, together with an emotional consistency loss to maintain emotional authenticity.

Question 3

What performance improvements and evaluation outcomes are reported for GAN-AraEmo?

Accepted Answer

On three Arabic emotional speech datasets it reaches 91.2% recognition accuracy versus 67.5% for a baseline, with synthetic samples achieving 4.2/5.0 mean opinion score and 94.3% emotional authenticity in human evaluation, plus stronger cross-dialect generalization.