Target Domain Corpus

A target domain corpus is a collection of text data specifically representative of a particular application area, used to improve the performance of machine learning models in that domain. Current research focuses on leveraging target domain corpora to enhance various natural language processing tasks, including translation, information extraction, and speech recognition, often employing large language models (LLMs) and transformer-based architectures for improved accuracy and efficiency. This work addresses the limitations of training models on general-purpose datasets by enabling better adaptation to specialized domains with limited labeled data, leading to more effective and cost-efficient model development across diverse applications.