In this research, we propose a complete set of approaches for identifying and extracting emotions from Bangla texts. We provide a Bangla emotion classifier for six classes: anger, disgust, fear, joy, sadness, and surprise, from Bangla words using transformer-based models, which exhibit phenomenal results in recent days, especially for high-resource languages. The Unified Bangla Multi-class Emotion Corpus (UBMEC) is used to assess the performance of our models. UBMEC is created by combining two previously released manually labeled datasets of Bangla comments on six emotion classes with fresh manually labeled Bangla comments created by us. The corpus dataset and code we used in this work are publicly available.

翻译：在本研究中，我们提出了一套完整的方法，用于从孟加拉语文本中识别和提取情感。我们利用基于Transformer的模型，从孟加拉语词汇中构建了一个包含六类情感（愤怒、厌恶、恐惧、喜悦、悲伤和惊讶）的孟加拉语情感分类器。此类模型在近期展现出卓越性能，尤其适用于高资源语言。我们采用统一孟加拉语多类情感语料库（UBMEC）来评估模型性能。该语料库通过整合两个先前发布的人工标注孟加拉语评论数据集（涵盖六类情感）与我们自行创建的新人工标注孟加拉语评论而构建。本研究所用的语料库数据集及代码均已公开提供。