Stella Laurenzo

Leveraging Weakly Supervised Data to Improve End-to-end Speech-to-text Translation

End-to-end Speech Translation (ST) models have many potential advantages when compared to the cascade of Automatic Speech Recognition (ASR) and text Machine Translation (MT) models, including lowered inference latency and the avoidance of error compounding. However, the quality of end-to-end ST is o…