Their strategies might be familiar to regular commuters . For example , they would plan their journeys with an app , arrive early and look for signage to let them know if anything had changed .
But they also said they felt they needed to stand near information screens to watch for updates , and ask station staff or other passengers for information when the situation had changed . They also reported being hypervigilant while on the train , watching to make sure they don ’ t miss their stop .
But these strategies didn ’ t always ensure Deaf travellers received important information , including about emergencies . For example , while usually helpful , station staff were sometimes too busy to assist .
The greatest frustration came in situations where other passengers weren ’ t willing or able to provide information , leaving our Deaf travellers to just “ follow the crowd ”. This often meant ending up in the wrong place .
Developing a signing avatar
Speech-to-text software might seem like an easy solution to some of these problems . But for many Deaf people , English is not their native language and Auslan can be processed far more easily and quickly .
Our Deaf travellers told us that , in a perfect world , they would want live interpreters . However , automatic , AI-powered translation using a signing avatar displayed on a platform or train screen which could identify key words in an audio announcement , generate a sentence with correct Auslan grammar , and stitch together the corresponding signs from our vocabulary library was appealing for a number of reasons .
First , it allows for real-time translation of announcements that use known vocabulary – which is relevant in the trains-andstations context , where many announcements cover similar topics .
Second , an avatar and its signing can be customised to the needs of a given situation , such as using information about screen location to ensure the avatar signs in the right direction while pointing out exits or other platforms .
Third , multiple signers can contribute signs to an avatar ’ s vocabulary , which can then be smoothly stitched together to make a sentence .
And importantly , an avatar means no real person has to be the “ face ” of an organisation ’ s automatically generated announcements . This is particularly important because the Australian Deaf community is small and close knit , and if something goes wrong with the translation , nobody suffers any reputational damage .
From a technical point of view , an avatar also allows us to ensure a minimum quality threshold for signing . We ’ re using motion capture to make sure each sign in our vocabulary library is accurate , and movements are clear .
It also helps us avoid the “ uncanny valley ” – an effect where something human-like but subtly wrong is unsettling . We don ’ t want any of the many-fingered monstrosities you may have seen recently generated by AI .
AI for everyone
This work is one step in our broader aim of creating an AI system which can understand Auslan . This AI could be used to help Deaf and hearing station staff converse , or to create “ chatbot booths ” or appbased assistants that would allow Deaf people to get information on demand in Auslan about their train journeys or other daily tasks .
Sign languages and Deaf cultures around the world have nuances and complexities that hearing researchers and developers of AI may not be aware of . These nuances and complexities must be embedded in new technologies , and researchers and developers must take a language-first approach to AI data collection and design with – not just for – Deaf people .
Only then will AI meet Deaf people ’ s real needs : to ensure their safety and independence in every aspect of daily life .
This article was originally published in The Conversation . Read the original article here .
For a Deaf traveller . . . when something out of the ordinary happens , the situation can quickly get scary , because most updates are only delivered by audio announcements .
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