Japanese Corpus

Japanese corpora are collections of Japanese language data used to train and evaluate computational linguistics models, addressing the need for large, diverse datasets in a language with unique linguistic properties. Current research focuses on creating corpora for various tasks, including spoken dialogue modeling, linguistic acceptability judgment, shout detection, and empathetic dialogue synthesis, often employing deep learning architectures like Connectionist Temporal Classification (CTC) and leveraging multimodal context information for improved performance. These resources are crucial for advancing natural language processing (NLP) in Japanese, enabling improvements in speech recognition, text-to-speech synthesis, and other applications requiring accurate and nuanced understanding of the language. The availability of high-quality, publicly accessible corpora is driving significant progress in the field.