Cross Lingual Speech Representation

Cross-lingual speech representation aims to create computational models that understand and process speech across multiple languages, overcoming the limitations of monolingual systems. Current research focuses on developing large-scale, self-supervised models like XLS-R and its derivatives (e.g., DistilXLSR), which leverage massive multilingual datasets to learn shared representations, improving performance in low-resource languages. These advancements significantly enhance automatic speech recognition, speech translation, and other speech-related tasks, promoting broader accessibility and inclusivity in speech technology.