Persona – Amber, activist for inclusive education.

Amber

young female face with whispy hair eyes looking down

Age: 23 years

Course: Computer Science 2nd Year

Hobbies: Yoga, running, actively taking part in lobbying for inclusion

Background:

Amber loves her yoga and running, excelling at school where she enjoyed an inclusive educational setting despite her severe bilateral hearing loss.  She is a hearing aid user and depends on lip reading (speech reading) and Sign Language, but speaks relatively clearly.  In fact, her communication skills are remarkable, thanks to the early and continuous support she received from her parents, both mathematics professors.  Nevertheless, being at university was quite a challenge in the early months.  She admitted to feeling isolated, but used her yoga and cross-country running activities to get her through.  She explained that the psychological and emotional feelings were almost more challenging than dealing with lectures, tutorials or trying to access support, plus she missed her family and friends in the Deaf community.  It was the constant need to explain to people why she had not heard them or put up with their replies “Oh it doesn’t matter, it’s not important” if she queried what had been said – her disability was non-visible The process of disambiguation can be very tiring and as Ian Noon said in his blog

“Processing and constructing meaning out of half-heard words and sentences. Making guesses and figuring out context. And then thinking of something intelligent to say in response to an invariably random question. It’s like doing jigsaws, Suduku and Scrabble all at the same time.”

Amber joined the Student Union and found fellow activists who became friends as well as lobbyists for disability awareness and more inclusive teaching practices.

Those who could use sign language were rare, although help was available from interpreters during lectures and at other times, from note takers.  Sometimes, Amber depended on fellow students’ notes, because it was hard to write, as well as concentrate on the lecturer or interpreter.  Giving a lecturer her FM transmitter and microphone helped, especially when they turned away to write on a board or there were discussions and noise levels were raised.  When lecture capture was in use, Amber always hoped the Automatic Speech Recognition (ASR) would provide good quality closed captions and subject specific words would be transcribed correctly.   During the COVID-19 pandemic, Amber used text-based Q&As and comments when events happened in real-time with captions or subtitles and transcripts if available.  Downloadable summaries and slide notes provided details missed on the video recording. Help and documentation about caption position adjustments, the text size and colour plus other settings for the conferencing system and access to a glossary of important subject related vocabulary has also been invaluable to aid comprehension.

Main Strategies to overcome Barriers to Access

Structured content 
Signing on videos – Personalising alternative format content
Multifactor authentication
Document Accessibility
Audible Error or Alert Messages must be inclusive with alternatives
Multimedia content needs captions that are accurate and synchronised with the audio.

Multifactor authentication Amber has found that the best way for her to overcome the multifactor authentication issues is to use text messages (SMS) with a onetime password (OTP) plus a smart phone app.  She has also found that finger biometrics on her phone helps with authentication or using an email system.  She has a card reader for her bank but does not use speech recognition or voice calls for any verification, as she is never sure if she is going to get an accurate result or hear everything. (Web Content Accessibility Guidelines (WCAG) 2.2 Success Criterion 3.3.7 Accessible Authentication)

Multimedia content needs captions that are accurate and synchronised with the audio. Video and audio output complement so much of web content and Amber depends on good quality alternatives to make services both usable and accessible. It is not just the content, but also the way players work and the fact that any audio needs to be controlled and not start automatically.  WCAG Guideline 1.2 – Time-based Media discusses content challenges and User Agent Accessibility Guidelines (UAAG) 2.0 provides technical details for developers such as Guideline 1.1 – Alternative content. The Authoring Tool Accessibility Guidelines (ATAG) also for developers and designers include the following guides related to those who have hearing impairments:

Signing on videos – Personalising alternative format content.  Being able to adjust the position of the window with interpreter signing and/or captions may be important when content is filling the screen in different places as seen in the YouTube lecture on Beginning Robotics provided by University of Reading.  Further guidance is available in their blog on Personalisation of viewing

Structured content is important for everyone and helps Amber when she needs to pick out key topics.  So clear headings and sub headings, use of white space and links to summaries, especially if they are related to video and transcript content, so she can see what is relevant to her needs.   So regions, headings and lists all help to make a content more understandable.

Audible Error or Alert Messages must be inclusive. Notifications need to be available as very visible alerts as well as being audible and, on a phone or electronic watch, this can also be via vibration.  

Document accessibility is important whether it is related to providing summaries and clear language or heading structure and bullet points, the aim is to make documents usable as well as accessible.   WebAim have an easy to follow set of instructions for making ‘Accessible Documents: Word, PowerPoint, & Acrobat’.

Key points from Amber

“I am a very visual person and I like to see a detailed process as a diagram or image – step by step.  I also really like having PowerPoint slides with all the main points…”

Interviews with Three Deaf Software Engineers in Bay Area (USA) Facebook video

TPGi provided a very helpful set of articles around an interview with Ruth MacMullen, who is an academic librarian and copyright specialist from York in the UK, called  “Sounding out the web: accessibility for deaf and hard of hearing people”  Part 1 and Part 2

The latest version of the iPhone operating system iOS 14 offers more accessibility options and personalisation with increased use of visual and vibrating alerts and further support for hearing aids

The “PacerSpacer” – Simplicity in Controlling the Pace of Presentation Software (like PowerPoint) “One of the most important things you can do for Deaf/HH audience members when using presentation software such as PowerPoint is to allow sufficient time for them to read the slides before you begin talking. For Deaf/HH individuals, this means allowing time for them to stop watching the interpreter or you, switch their attention to a slide, and then return their attention to either the interpreter or you. With an interpreter, even more time is required since there is a lag time between what you say and the signing of that message.” DeafTec, Rochester Institute of Technology (USA)

Transcripts from Captions?

young person looking at computer for online learning

The subject of automatic captioning continues to be debated but Gerald Ford Williams has produced a really helpful “guide to the visual language of closed captions and subtitles” on UX Collective as a “user-centric guide to the editorial conventions of an accessible caption or subtitle experience.” It has a series of tips with examples and several very useful links at the bottom of the page for those adding captions to videos. There is also a standard for the presentation of different types of captions across multimedia ISO/IEC 20071-23:2018(en).

However, in this article transcripts are something that also need further discussion, as they are often used as notes gathered from a presentation, as a result of lecture capture or an online conference with automatic captioning. They may be copied from the side of the presentation, downloaded after the event or presented to the user as a file in PDF/HTML or text format depending on the system used. Some automated outputs provide notification of speaker changes and timings, but there are no hints as to content accuracy prior to download.

The problem is that there also seem to be many different ways to measure the accuracy of automated captioning processes which in many cases become transcriptions. 3PlayMedia suggest that there is a standard, saying “The industry standard for closed caption accuracy is 99% accuracy rate. Accuracy measures punctuation, spelling, and grammar. A 99% accuracy rate means that there is a 1% chance of error or a leniency of 15 errors total per 1,500 words” when discussing caption quality.

The author of the 3PlayMedia article goes on to illustrate many other aspects of ‘quality’ that need to be addressed, but the lack of detailed standards for the range of quality checks means that comparisons between the various offerings are hard to achieve. Users are often left with several other types of errors besides punctuation, spelling and grammar. The Nlive project team have been looking into these challenges when considering transcriptions rather than captions and have begun to collect a set of additional issues likely to affect understanding. So far, the list includes:

  • Number of extra words added that were not spoken
  • Number of words changed affecting meaning – more than just grammar.
  • Number of words omitted
  • Contractions … e.g. he is – he’s, do not … don’t and I’d could have three different meanings I had, I would, or I should!

The question is whether these checks could be included automatically to support collaborative manual checks when correcting transcriptions?

Below is a sample of the text we are working on as a result of an interview to demonstrate the differences between three commonly used automatically generated captioning systems for videos.

Sample 1

Sample 2

Sample 3

So stuck. In my own research, and my own teaching. I’ve been looking at how we can do the poetry’s more effectively is one of the things so that’s more for structuring the trees, not so much technology, although technology is possibleso starting after my own research uh my own teaching i’ve been looking at how we can do laboratories more effectively is one of the things so that’s more for structuring laboratories not so much technology although technology is part of the laboratoryso stop. In my own research on my own teaching, I’ve been looking at how we can do the ball trees more effectively. Is one thing, so that’s more for structuring the voluntary is not so much technology, although technology is part little bar tree

Having looked at the sentences presented in transcript form, Professor Mike Wald pointed out that Rev.com (who provide automated and human transcription services) state that we should not “try to make captions verbatim, word-for-word versions of the video audio. Video transcriptions should be exact replications, but not captions.” The author of the article “YouTube Automatic Captions vs. Video Captioning Services” highlights several issues with automatic closed captioning and reasons humans offer better outcomes. Just in case you want to learn more about the difference between a transcript and closed cations 3PlayMedia wrote about the topic in August 2021 “Transcription vs. Captioning – What’s the Difference?”.

Subtitles for translating video content – English not your first language?

“When you watch videos that are not in your first language – if there are subtitles turn these into your chosen language to help explain the content.”

turning on captions

YouTube has closed captioning or subtitles on some videos and the video called “How to extract YouTube Subtitles (Interactive Transcript) in 2 minutes [HD]” illustrates some of the difficulties that occur with automatic captioning – A Frenchman speaking in English and when you view the subtitles by selecting the small list icon on the bottom right of the video player you will see that some of the words do not match what has been said but you can also translate the words into your chosen language.  The results will be variable!  In this video you will see how you can take the transcript and improve the results.