# Rethinking Cross-Corpus Speech Emotion Recognition Benchmarking: Are Paralinguistic Pre-Trained Representations Sufficient?

arXiv: https://arxiv.org/abs/2509.16182 · HTML: https://mlsanity.com/paper/2509.16182/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2025.

## Built on by (most cited first, 1 of 1)

- [VoxEmo: Benchmarking Speech Emotion Recognition with Speech LLMs](https://mlsanity.com/paper/2603.08936/) (2026)

## Abstract (arXiv)

Recent benchmarks evaluating pre-trained models (PTMs) for cross-corpus speech emotion recognition (SER) have overlooked PTM pre-trained for paralinguistic speech processing (PSP), raising concerns about their reliability, since SER is inherently a paralinguistic task. We hypothesize that PSP-focused PTM will perform better in cross-corpus SER settings. To test this, we analyze state-of-the-art PTMs representations including paralinguistic, monolingual, multilingual, and speaker recognition. Our results confirm that TRILLsson (a paralinguistic PTM) outperforms others, reinforcing the need to consider PSP-focused PTMs in cross-corpus SER benchmarks. This study enhances benchmark trustworthiness and guides PTMs evaluations for reliable cross-corpus SER.