论文标题
交叉语言交叉语料库语音情感识别
Cross Lingual Cross Corpus Speech Emotion Recognition
论文作者
论文摘要
现有的大多数语音情感识别模型都经过单个语料库和单语言设置进行了培训和评估。当在跨语言和跨语言场景中应用时，这些系统的性能不佳。本文介绍了单个语料库和交叉语料库设置中4种语言的语音情感识别的结果。此外，由于具有性别，自然性和唤醒作为辅助任务的多任务学习（MTL）已显示出可以增强情感模型的概括能力，因此本文将语言ID作为MTL框架中的另一个辅助任务介绍，以探索尚未研究过尚未研究的语言识别的作用。
The majority of existing speech emotion recognition models are trained and evaluated on a single corpus and a single language setting. These systems do not perform as well when applied in a cross-corpus and cross-language scenario. This paper presents results for speech emotion recognition for 4 languages in both single corpus and cross corpus setting. Additionally, since multi-task learning (MTL) with gender, naturalness and arousal as auxiliary tasks has shown to enhance the generalisation capabilities of the emotion models, this paper introduces language ID as another auxiliary task in MTL framework to explore the role of spoken language on emotion recognition which has not been studied yet.
