构建多语言情感语音数据集，助力情绪识别研究与评测。
CAMEO: Collection of Multilingual Emotional Speech Corpora
- 精选多语言情感语音数据，统一格式与标注标准。
- 提供基准测试平台与排行榜，支持跨语言情绪识别评估。
- 数据集公开可获取，推动研究可复现性与公平对比。
本文提出CAMEO——一个精心整理的多语言情感语音数据集集合，旨在促进情绪识别及其他语音相关任务的研究。主要目标包括确保数据易获取、结果可复现，并为跨情感状态与语言的情绪语音识别（SER）系统提供标准化评测基准。论文详述了数据集筛选标准、数据清洗与归一化流程，并报告了多个模型的性能表现。该数据集连同元数据及排行榜已通过Hugging Face平台公开发布。
原文摘要 · Abstract (English)
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.
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