How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation
  System?
Authors: name: Sara Papi, name: Peter Polak, name: Ondřej Bojar, name: Dominik Macháček

Simultaneous speech-to-text translation (SimulST) translates source-language
speech into target-language text concurrently with the speaker's speech,
ensuring low latency for better user comprehension. Despite its intended
application to unbounded speech, most research has focused on human
pre-segmented speech, simplifying the task and overlooking significant
challenges. This narrow focus, coupled with widespread terminological
inconsistencies, is limiting the applicability of research outcomes to
real-world applications, ultimately hindering progress in the field. Our
extensive literature review of 110 papers not only reveals these critical
issues in current research but also serves as the foundation for our key
contributions. We 1) define the steps and core components of a SimulST system,
proposing a standardized terminology and taxonomy; 2) conduct a thorough
analysis of community trends, and 3) offer concrete recommendations and future
directions to bridge the gaps in existing literature, from evaluation
frameworks to system architectures, for advancing the field towards more
realistic and effective SimulST solutions.