Module code: TRAM506

Module Overview

The main purpose of this module is to acquaint students with specific knowledge, skills and competences that are relevant to make live content (e.g. speeches, audiovisual content) accessible in real time and across languages in the form of live subtitles that cater for a broad audience (including d/Deaf and Hard-of-Hearing as well as other language speakers). This is an optional module for students wanting to apply the language transfer and interpreting skills acquired in their language-specific practices to emerging hybrid workflows with a great potential for societal impact and for remaining relevant and future-proof in the fast-developing language services industry.

Module provider

School of Literature and Languages

Module Leader

DAVITTI Elena (Lit & Langs)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Workshop Hours: 12

Independent Learning Hours: 108

Seminar Hours: 10

Guided Learning: 10

Captured Content: 10

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

This module will introduce students to the procedural, cognitive and analytical skills required to carry out real-time speech-to-text communication through interaction with speech recognition.

The module will explore existing workflows to produce live subtitles within and across languages, placing emphasis on their affordances and constraints, and on current uses, based on industry insights. This is a pioneer module, in that it broadens students' horizons about techniques and practices currently under development to give them a competitive advantage in the world of work.

The module will teach students fundamental skills to perform live subtitling via respeaking, both intra and interlingually (i.e. within the same and across different languages), how to capitalize on skills already acquired through other practical modules (e.g. interpreting, translation) and what to adjust to be able to effectively interact with speech recognition and produce accurate output. The module will also cover how to analyse different types of (audiovisual) content, how to prepare effectively for an assignment, what to consider when crossing modalities and moving from spoken input to written output. Hands-on practice will be performed both in class and as part of independent study, with state of the art and industry standard software.

Materials used will cover real-life scenarios and present recurring challenges to provide students with a competitive edge. The common working language will be English, but students will also work into their A language, as they do in their translation and interpreting classes. Where there is no SR technology available in the students¿ A language arrangements will be made to work into English from their mother tongue, which is common across all interpreting modules. Choosing this module as part of the curriculum will enhance students' skillset and contribute to further expanding the portfolio of services they will be able to offer in the future. Combined with the expertise acquired through other programme modules, this module will train future-proof graduates able to navigate a constantly evolving industry and educate clients about different options available to make content accessible to the widest possible audience, across languages and cultures.

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Reflective report (1,500-2,000 words) 40
Coursework Assignment of live speech-to-text communication 60

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their procedural, cognitive and analytical skills, alongside the other module outcomes, in relation to hybrid practices for live speech-to-text communication via speech recognition. This will be achieved via both formative assessment (ongoing throughout the module) and summative assessment. Through this strategy, this module empowers students to build self-monitoring and self-evaluation into assessment process and creates space for them to reflect and critically comment on own performance. Also, students are encouraged to identify which aspect(s) of their work they would like to request feedback, thus developing them into independent learners.

  • One assignment of consecutive interpreting into the student's A language at the end of the semester

  • One reflective presentation about the consecutive interpreting assignment, including a presentation by the student and follow up-questions at the end of the semester

 Thus, the summative assessment for this module consists of:

  • One reflective report (1,500-2,000 words) about the performance, including evaluation of the target output via learned quality assurance metrics and explanation of the challenges encountered, strategies used to cope with them and reflection on what could have been done differently (40% addresses learning outcomes 1, 3, 6).

  • One assignment of live speech-to-text communication, partly intralingual and partly interlingual at the end of the semester (60%, addresses learning outcomes 2, 4, 5)

Formative assessment and feedback:

Students will receive regular comprehensive feedback and feedforward from tutors and peers on their preparation and skills during the practice in class, which allows them to monitor their progress week by week. As part of their self-practice, they will be encouraged to keep a portfolio of their activities and log their reflections, and there will be opportunities for short outside classroom 'clinics' for students to select specific parts from their portfolio that they considered challenging or would like extra (verbal) feedback on and discuss them with tutors on a one-to-one basis. Towards the end of the semester, students conduct a formative 'mock exam' to simulate their end-of-semester assignment. This includes comprehensive feedback, an indicative mark and feed-forward to enable students to prepare for the end-of-semester assignment. In the mock exam, the same assessment criteria as the end-of-semester assignment will be used. The criteria are made available to and explained to the students in class.

Module aims

  • This module aims to: develop a thorough grasp and theoretical understanding of the panorama of live speech-to-text practices, including what workflows are used in the industry, what professional settings and needs they cater for and how this fast-changing industry evolves over time
  • help students to gradually acquire the skills and strategies necessary to develop practical expertise in delivering live subtitling both intra and interlingually (i.e. in the same and in another language) through the technique of respeaking, by means of available speaker-dependent speech-recognition technology
  • help students to prepare for professional practice in a wide variety of situations, through critical reflection upon different scenarios and needs where this service may be required
  • understand and apply different types of quality assurance metrics to assess and evaluate critically the extent to which specific live speech-to-text processes and outputs are fit for purpose
  • encourage students to develop reflective and critical skills and a thorough understanding of these practices and their implications in various scenarios via in class discussions and analysis of own and other performance in different situations

Learning outcomes

Attributes Developed
001 In this module, you will: develop understanding and awareness of different hybrid practices for live speech-to-text communication and of their advantages and limitations in different scenarios. KP
002 Develop procedural skills to grasp, process and transfer spoken (audiovisual) content in the form of live subtitles via direct interaction with speech recognition technology both intralingually (i.e. in one language) and interlingually (i.e. in another language) CP
003 Apply essential live speech-to-text communication principles and conventions and quality assurance metrics to evaluate and self-monitor performance within a range of real-life materials presenting recurring challenges. CP
004 Identify the challenges of different source text materials and workflows and demonstrate the strategies needed (e.g. editing, condensing) and research skills necessary to prepare both yourself and the machine for an assignment in the most efficient way, through a variety of resources and techniques KCP
005 Develop resilience and self-efficacy as well as the ability to work effectively and thrive under pressure and apply knowledge acquired about speech-recognition technology and different technological solutions to solve contingent problems CPT
006 Appraise information and communication technologies (e.g. speech recognition, machine translation) and the challenges they create for hybrid practices for live speech-to-text communication KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

  • Combine teacher-led input and discussion (approx. 40%) and hands-on activities (approx. 60%) allowing for extensive practice using the department¿s facilities and state-of-the-art technology.

  • Enable collaborative learning through a combination of (tutor-led and peer-supported) seminars and workshop hours during which students will be encouraged to discuss with their peers and develop their practical skills in small groups workshops.

  • Encourage critical self- and peer- evaluation of their own performance and give students confidence in the fundamentals of these hybrid practices, regardless of academic background, allowing them to adjust their skillset and develop all relevant skills required.

The learning and teaching methods selected for this course are strongly informed by findings from research carried out within the Centre for Translation Studies, within the research strand on hybrid practices for real-time speech-to-text communication.

The learning and teaching methods include:

  • Tutor-led seminar sessions to develop knowledge and awareness of different practices, techniques, needs and uses around accessibility to content in real time and for different user bases. These will be done in language-pair independent fashion, through active learning activities, guided practice, demonstrations and discussions aimed to encourage the sharing of views on the principles and needs to create access in different ways and according to different needs, across languages and cultures.

  • Small-group practice workshops that enable students to apply and refine their practical skills through hands-on practice and receive a large amount of formative feedback from their tutors and peers. Workshops include opportunities for hands-on practice with simulated real-life materials, thus enabling students to put their knowledge into practice and develop additional key technical and transferrable skills (e.g. teamwork, professionalism), as well as first-hand awareness of the cognitive challenges embedded in these practices, preparing them for the world of work.

  • Self-practice (a minimum of 6 hours per week) during which students are expected to apply and finetune their skills and independent study (a minimum of 4 hours per week) during which students are expected to research the subject areas and develop digital and research skills to enable them to prepare at best for an assignment, including efficient preparation of speech recognition technology involved. Students are also expected to contribute to finding appropriate materials for their specific language pairs, under the tutor's guidance, and to spend a significant amount of time practicing, individually and, where possible, in small groups, as well as monitor own performance on the basis of the quality assurance metrics taught during the course. To this end, regular recording of own performance and logging of progress will be expected throughout the course, to enhance different aspects of performance via reflective analysis.

  • Students are encouraged to be active participants throughout the practical sessions, and support one another during the process, and in doing so, develop as informed, confident, collaborative and independent learners. They are also be expected to prepare in advance of each class in terms of research and keep up with the readings provided.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

Upon accessing the reading list, please search for the module using the module code: TRAM506

Other information

Surrey's Curriculum Framework is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills and capabilities in a range of areas.

This module, which is shared by all CTS-offered MA programmes, provides students with fundamental knowledge and awareness about different practices for live speech-to-text communication via speech recognition, including key concepts underpinning emerging hybrid practices, and prepares them for acquiring basic practical skills and competences, in a gradual and incremental way and via blended and scaffolded learning. To this end, it builds on the skills acquired by students in the various practice-based modules acquired by students on their own respective MA programme, and teaches students how to capitalize on and adjust them to the new, hybrid practices under exploration. All these skills are highly professionalizing and geared towards making students employment-ready when finishing their degree, as well as opening up new possibilities to remain relevant in the rapidly evolving language industry, thus boosting diversification and sustainability in the professional market. This module also teaches students how to reflect on their own practice, with a view to developing awareness and coping strategies, thus increasing resourcefulness and resilience. It will also enhance students' awareness of how these practices need to be adjusted to different linguistic and cultural contexts, thus enhancing their global and cultural capabilities. The module will also develop students' digital skills by teaching them specific forms of human-machine interaction and encouraging them to become proficient at assessing and preparing efficiently different types of technologies for the purpose of live speech-to-text communication.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Interpreting MA 2 Optional A weighted aggregate mark of 50% is required to pass the module
Translation and Interpreting MA 2 Optional A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.