Speech emotion recognition has become increasingly important in recent years due to its potential applications in healthcare, customer service, and personalization of dialogue systems. However, a major issue in this field is the lack of datasets that adequately represent basic emotional states across various language families. As datasets covering Slavic languages are rare, there is a need to address this research gap. This paper presents the development of nEMO, a novel corpus of emotional speech in Polish. The dataset comprises over 3 hours of samples recorded with the participation of nine actors portraying six emotional states: anger, fear, happiness, sadness, surprise, and a neutral state. The text material used was carefully selected to represent the phonetics of the Polish language adequately. The corpus is freely available under the terms of a Creative Commons license (CC BY-NC-SA 4.0).

翻译：摘要：语音情感识别近年来因在医疗保健、客户服务及对话系统个性化等领域的潜在应用而日益重要。然而，该领域面临的主要问题是缺乏能充分代表不同语系基本情感状态的数据集。由于涵盖斯拉夫语系的数据集极为罕见，亟需填补这一研究空白。本文介绍了nEMO语料库的构建——一个全新的波兰语情感语音数据集。该数据集包含超过3小时的样本，由九位演员录制，演绎六种情感状态：愤怒、恐惧、快乐、悲伤、惊讶及中性状态。所用文本素材经过精心筛选，以充分体现波兰语的语音特征。本语料库在知识共享许可协议（CC BY-NC-SA 4.0）条款下免费开放使用。