Simultaneous Speech Translation for Live Subtitling: from Delay to Display

Alina Karakanta, Sara Papi, Matteo Negri, Marco Turchi


Abstract
With the increased audiovisualisation of communication, the need for live subtitles in multilingual events is more relevant than ever. In an attempt to automatise the process, we aim at exploring the feasibility of simultaneous speech translation (SimulST) for live subtitling. However, the word-for-word rate of generation of SimulST systems is not optimal for displaying the subtitles in a comprehensible and readable way. In this work, we adapt SimulST systems to predict subtitle breaks along with the translation. We then propose a display mode that exploits the predicted break structure by presenting the subtitles in scrolling lines. We compare our proposed mode with a display 1) word-for-word and 2) in blocks, in terms of reading speed and delay. Experiments on three language pairs (en→it, de, fr) show that scrolling lines is the only mode achieving an acceptable reading speed while keeping delay close to a 4-second threshold. We argue that simultaneous translation for readable live subtitles still faces challenges, the main one being poor translation quality, and propose directions for steering future research.
Anthology ID:
2021.mtsummit-asltrw.4
Volume:
Proceedings of the 1st Workshop on Automatic Spoken Language Translation in Real-World Settings (ASLTRW)
Month:
August
Year:
2021
Address:
Virtual
Venue:
MTSummit
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
35–48
Language:
URL:
https://aclanthology.org/2021.mtsummit-asltrw.4
DOI:
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.mtsummit-asltrw.4.pdf
Code
 sarapapi/reading_speed
Data
MuST-Cinema