Speech Translation Corpus

Speech translation corpora are collections of parallel audio and text data in multiple languages, crucial for training and evaluating automatic speech translation (ST) systems. Current research focuses on improving data quality and quantity, including creating new corpora for low-resource languages and code-switching scenarios, and developing techniques to augment existing datasets using methods like segmentation and synthetic data generation. These efforts leverage various model architectures, such as transformer-based neural networks and large language models, to enhance translation accuracy and efficiency. The development of high-quality speech translation corpora is vital for advancing ST technology, impacting fields like court reporting, simultaneous interpretation, and cross-lingual communication.