Intralingual Subtitling

• Get theoretical knowledge and be able to work hands-on with professional software
• Become more sensitive to and understand the specifics of the audiovisual translation process of subtitling as a form of semiotic transfer
• Learn the basic functions of the professional software required to generate intralingual subtitles that are optimally adapted to the needs of the respective target groups
• Conduct a subtitling project to ensure the transfer from theory to practice

Freelance and employed translators in various institutions and companies, such as language service providers, translation agencies and media broadcasters. General language, media and accessibility professionals and participants with a languages background

Day 1 | Basics

Theory

•   Audiovisual translation: semiotics, multimodality, and communication channels – the film medium as source text
•   Subtitling: production and reception from a target group perspective – the subtitles as target text
•   Standards, guidelines, practical recommendations
•   Technical and linguistic aspects, as well as their restrictions in the context of subtitling

Practice

Hands-on : Subtitling project – Part 1

Technology:

•   Insights into subtitling software and how to use basic functions and tools
•   Project creation: file formats and settings
•   Subtitle creation: technical insertion and adjustment of time codes

Linguistics :

•  Text strategies for subtitle creation

 

Day 2 | Deep Dive

Theory

• Textual segmentation for optimising readability and comprehensibility
• Revision and quality assurance
• State-of-the-art: harnessing artificial intelligence and machine learning – potentials of speech recognition and automatic subtitle generation
• Beyond tradition: current and future trends – immersive media and new job profiles in the audiovisual media sector

Practice

Hands-on : Subtitling project – Part 2

• Group discussion of the subtitling project after Day 1 

Technology :

• How to use quality assurance tools
• Post-editing and the evaluation of automatically generated transcripts and subtitles using speech recognition-based subtitling software

Linguistics :

• Text segmentation and adaptation for subtitle optimisation

A certificate of participation is issued to those who have completed the training.

Contact coordinator

CHF 1,000.-
 

The training will be conducted entirely remotely by zoom.

 

Wednesday 16 and 23 November 2022 | 10 am – 1 pm and 2 pm – 5 pm

The demand for subtitling is steadily increasing worldwide. National and international (legal) requirements for accessibility in the public sector, together with the private sector’s interest in making information in videos available to a wider audience, are the driving forces behind this development.
Intralingual subtitles also allow improved text information retrieval in relation to modern search engine optimisation (SEO) and search engine marketing (SEA).
However, there is often a lack of theoretical, and especially practical knowledge of video subtitling. In our two-day workshop, you will not only learn about audiovisual translation, but also how intralingual subtitling, i.e., subtitling projects within the same language, can be successfully implemented for target groups in varying contexts.

Alexander Kurch has been working as an audiovisual translator for accessibility since 2013, including speech-to-text interpreting (live texting for people with and without hearing impairment), intralingual and interlingual subtitling, audio description (authoring of audio film versions for people with visual impairments) and post-editing for artificial voices.

He studied translation studies at the University of Heidelberg and at the Dublin City University, and media translation at the University of Hildesheim. Besides his practical experience, he is active as an independent researcher, freelance lecturer, trainer and auditor for accessibility in audiovisual translation. His special focus is on synergies of accessible communication in combination with (language) technologies and machine learning, such as speech recognition, machine translation, and speech synthesis including post-editing and evaluations of quality and efficiency.