CAMEO: Collection of Multilingual Emotional Speech Corpora

TL;DR

CAMEO is a publicly available, multilingual emotional speech dataset collection designed to standardize and facilitate research in speech emotion recognition across different languages and emotional states.

Contribution

This work introduces a curated, normalized collection of multilingual emotional speech datasets with a benchmark and leaderboard for SER research.

Findings

Performance results for several models on the dataset

Standardized benchmark for multilingual SER

Accessible via Hugging Face platform

Abstract

This paper presents CAMEO -- a curated collection of multilingual emotional speech datasets designed to facilitate research in emotion recognition and other speech-related tasks. The main objectives were to ensure easy access to the data, to allow reproducibility of the results, and to provide a standardized benchmark for evaluating speech emotion recognition (SER) systems across different emotional states and languages. The paper describes the dataset selection criteria, the curation and normalization process, and provides performance results for several models. The collection, along with metadata, and a leaderboard, is publicly available via the Hugging Face platform.