title: How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation
    System?
summary: 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.
paper_authors._id: 676dbfe27fff9075b53888d4
paper_authors.name: Sara Papi
paper_authors.status: extracted_confirmed
paper_authors.statusLastChangedAt: 2024-12-26T20:48:59.504Z
paper_authors._id: 66309b3833ccd9e68c5d5171
paper_authors.avatarUrl: /avatars/bd2a3fb38820c828bdb1acb93b673cb4.svg
paper_authors.fullname: Sara Papi
paper_authors.type: user
paper_authors.user: spapi
paper_authors._id: 676dbfe27fff9075b53888d5
paper_authors.name: Peter Polak
paper_authors._id: 676dbfe27fff9075b53888d6
paper_authors.name: Ondřej Bojar
paper_authors._id: 676dbfe27fff9075b53888d7
paper_authors.name: Dominik Macháček
paper_title: How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation
    System?
paper_summary: 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.