Amharic Speech Emotion Dataset

Amharic speech emotion datasets are a crucial resource for advancing speech processing technologies in a low-resource language. Current research focuses on developing and improving these datasets, employing various deep learning architectures like VGG, ResNet, and LSTM for speech emotion recognition (SER) and exploring cross-lingual training strategies to leverage data from higher-resource languages. These efforts are significant because they address the scarcity of Amharic language resources, enabling advancements in applications such as hate speech detection, machine translation, and improved accessibility for Amharic speakers. The availability of these datasets and the resulting models contribute to a broader understanding of cross-lingual speech processing and its challenges.