Re Translation Strategies for Long Form, Simultaneous, Spoken Language Translation
We investigate the problem of simultaneous machine translation of long form speech content. We target a continuous speech to text scenario, generating translated captions for a live audio feed, such as a lecture or play by play commentary. As this scenario allows for revisions to our incremental translations, we adopt a re translation approach to simultaneous translation, where the source is repeatedly translated from scratch as it grows. This approach naturally exhibits very low latency and high final quality, but at the cost of incremental instability as the output is continuously refined. We experiment with a pipeline of industry grade speech recognition and translation tools, augmented with simple inference heuristics to improve stability. We use TED Talks as a source of multilingual test data, developing our techniques on English to German spoken language translation. Our minimalist approach to simultaneous translation allows us to scale our final evaluation to several other target languages, dramatically improving incremental stability for all of them.
ICASSP 2020 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)