PRE2020 3 Group6

Sign to text software

Group Members

Name	Student ID	Department	Email address
Ruben Wolters	1342355	Computer Science	r.wolters@student.tue.nl
Pim Rietjens	1321617	Computer Science	p.g.e.rietjens@student.tue.nl
Pieter Michels	1307789	Computer Science	p.michels@student.tue.nl
Sterre van der Horst	1227255	Psychology and Technology	s.a.m.v.d.horst1@student.tue.nl
Sven Bierenbroodspot	1334859	Automotive Technology	s.a.k.bierenbroodspot@student.tue.nl

Problem Statement and Objective

At the moment 466 million people suffer from hearing loss, it has been predicted that this number will increase to 900 million by 2050. Hearing loss has, among other things, a social and emotional impact on ones life. The inability to communicate easily with others can cause an array of negative emotions such as loneliness, feeling of isolation and sometimes also frustration !!!!!!!!!!!("Deafness and hearing loss", 2021)!!!!!!!! . Although there are many different types of speech recognition technologies for live subtitling that can help people that are deaf or hard of hearing (DHH), these feelings can still be exacerbated during online meetings. DHH individuals must concentrate on the person talking, the interpretation, and of any potential interruptions that can occur !!!!!!!!(Peruma & El-Glaly, 2017)!!!!!!!!!!. Furthermore, to be able to take part in the discussion, they must be able to spontaneously react in conversation. However, not everyone understands sign language which makes communicating even more difficult. Nowadays, especially due to the COVID-19 pandemic, it is becoming more normal to work from home and therefore the number of online meetings is increasing quickly !!!!!!!("Microsoft Teams reaches 115 million DAU—plus, a new daily collaboration minutes metric for Microsoft 365 - Microsoft 365 Blog", 2021)!!!!!!!!. This leads us to our objective: to deveop software that translates Sign Language to text to help DHH individuals communicate in an online environment. This system will be a tool that DHH individuals can use to communicate during online meetings. The number of people that have to work or be educated from home has rapidly increased due to the COVID-19 pandemic (European Commission, 2020). This means that the number of DHH individuals that have to work in online environments also increases. Previous studies have shown that DHH individuals obtain lower score on an Academic Engagement Form for communication compared to students with no disability (Richardson, Long, & Foster, 2004). This finding can be explained by the fact that DHH people are usually unable to understand speech without aid. This aid can be a hearing aid, technology that convert speech to text, or even an interpreter, however the latter is expensive and not available for most DHH individuals. To talk to or react to other people, DHH individuals can use pen and paper, or in an online environment by typing. However, this is a lot slower than speech or sign language which makes it almost impossible for DHH individual to keep up with the impromptu nature of discussions or online meetings (Glasser, Kushalnagar, & Kushalnagar, 2019). Therefore, by creating software that can convert sign language to text, or even to speech, DHH individuals will be able to actively participate in meeting. To do this, it is important to understand what sign language is. The following section of this wiki page, will explain the different elements of sign language and what it is.

Sign Language

https://books.google.nl/books?id=dnxDgCvEnJoC&lpg=PR11&ots=03dwMQ7zBO&dq=sign%20language&lr&pg=PA1#v=onepage&q=sign%20language&f=false

Design concepts

Technical specifications

Realization

Testing

Design evaluation

Week 1

Week 1 mostly consisted of putting together a group and decide upon a topic. We settled on the topic of emotion recognition on children with ASD. Research has been done on this topic and references to similar projects have been gathered. The focus for next week is to explore what is possible to achieve within this topic.

Name	Student ID	Hours	Description
Sven Bierenbroodspot	1334859	8,5	description
Sterre van der Horst	1227255	8,5	description
Pieter Michels	1307789		description
Pim Rietjes	1321617		description
Ruben Wolters	1342355		description

Week 2

In week 2 we decided after discussing the possible deliverables and came to the conclusion that it is difficult to find a dataset which we could use. The creation of a dataset is nearly impossible due to the slim target group and the current corona measures. for these reasons we abandoned the subject and discussed a new topic. The selected topic is to develop software which can convert sign language into text using video as an input.

Week 3

Research into the functioning of people suffering for hearing loss: http://www.werkenmeteenbeperking.nl/downloads/werkgeversboekje-dove-werknemer-pdf.pdf https://www.tolkcontact.nl/tolkcontact-app/wat-kun-je-met-de-app/ https://dl.acm.org/doi/abs/10.1145/3373625.3418032?casa_token=qBFFHzT_TIYAAAAA:5J8VJu4e5kn85EA339sWPTJ5NPrzG3dfX6VY5-DBertEQeKUk9xDEnSorUJ8S6svFsBRnxgdOI23M9U