ISub! Localization Workflows that Work

  • Massidda, Serenella (PI)

Project Details

Description

¡Sub!: Localisation Workflows that Work, is an international pilot project involving the University of International Studies (UNINT) in Italy and Roehampton University in the UK. The aim of the project is to analyse current practices in the AVT industry and compare different workflows and related technologies in order to identify the combination of human and technological factors able to produce ‘workflows that work’. More specifically, a series of experiments comparing workflows involving different combinations of CAT, MT and automatic speech recognition (ASR) tools will be conducted to devise the most efficient workflow equation: the best quality output in the tightest turnaround time. Subjects for the experiments, collaborating on subtitling projects carried out in teams, will be recruited among postgraduate students belonging to both universities. The audiovisual materials will be selected from among educational and science docuseries and documentaries in order to test the efficiency of the tools especially on the related LSP (language for special purposes). The present project will represent the opportunity to experiment on advanced technologies, test several tools, streamline research methodology and collect preliminary data from a relatively small group of subjects. Moreover, the results of the pilot study will be used to inform translator training practices, to ensure they are in line with constantly evolving market demands.

Layman's description

¡Sub!: Localisation Workflows that Work, an international pilot project aimed at analysing current practices in the AVT industry and compare different workflows and related technologies in order to identify the combination of human and technological factors able to produce ‘workflows that work’.
The present project will represent the opportunity to experiment on advanced technologies, test several tools, streamline research methodology and collect preliminary data from a relatively small group of subjects. Moreover, the results of the pilot study will be used to inform translator training practices, to ensure they are in line with constantly evolving market demands.

Key findings

translation subtitling technologies localization machine translation workflows ASR
Short titleISub!
AcronymISub!
StatusFinished
Effective start/end date31/01/2031/12/24

Keywords

  • Subtitling
  • Localization
  • Technologies
  • Machine Translation
  • Automatic Speech Recognition
  • Translation