How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation
  System?
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.
676dbfe27fff9075b53888d4
Sara Papi
extracted_confirmed
2024-12-26T20:48:59.504Z
66309b3833ccd9e68c5d5171
https://cdn-avatars.huggingface.co/v1/production/uploads/66309b3833ccd9e68c5d5171/UGt7pZazJHhtwjg0iiyBu.jpeg
Sara Papi
user
spapi
676dbfe27fff9075b53888d5
Peter Polak
676dbfe27fff9075b53888d6
Ondřej Bojar
676dbfe27fff9075b53888d7
Dominik Macháček
How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation
  System?
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.
Research on simultaneous speech-to-text translation focuses on pre-segmented speech, lacking standard terminology and addressing challenges for real-world applications.
speech-to-text translation SimulST low latency human pre-segmented speech standardized terminology taxonomy evaluation frameworks system architectures