Application Requirements for Deaf Students to use in Inclusive Classrooms

The goal was to search for an alternative to mediate communication between people who are Deaf or Hard of Hearing (D/HH) and hearing individuals, in which the major motivation was to provide empowerment for D/HH students, using technology to provide them with more autonomy in inclusive classrooms. With that in mind, a systematic literature review was conducted to elucidate requirements for a mobile application that includes a Speech-To-Text (STT) system, as well as an opinion research accomplished with D/HH participants to know potential users' priorities among the elucidated requirements. As a result, the preference to communicate in Libras (Brazilian Sing Language) prevails, although users consider important to use a mobile application as the one proposed.

[1]  Walter S. Lasecki,et al.  Legion scribe: real-time captioning by the non-experts , 2013, W4A.

[2]  Mike Wald,et al.  Synote: Important Enhancements to Learning with Recorded Lectures , 2012, 2012 IEEE 12th International Conference on Advanced Learning Technologies.

[3]  Walter S. Lasecki,et al.  Real-time captioning by groups of non-experts , 2012, UIST.

[4]  Lisa B. Elliot,et al.  Deaf and Hard-of-Hearing Students' Memory of Lectures with Speech-to-Text and Interpreting/Note Taking Services , 2009 .

[5]  Ma Jun,et al.  The Exploration of the Strategies and Skills of Effective Use of Voice Recognition Software in the Classroom for Deaf Students , 2010, 2010 Second International Conference on Future Networks.

[6]  Mike Wald.  Captioning for Deaf and Hard of Hearing People by Editing Automatic Speech Recognition in Real Time , 2006, ICCHP.

[7]  Seyed Ghorshi,et al.  Audio-visual speech recognition techniques in augmented reality environments , 2013, The Visual Computer.

[8]  WayThomas,et al.  Inclusion of deaf students in computer science classes using real-time speech transcription , 2007 .

[9]  Thomas Way,et al.  Achieving acceptable accuracy in a low-cost, assistive note-taking, speech transcription system , 2008 .

[10]  Elaine Pearson,et al.  Improving the accessibility of the traditional lecture: an automated tool for supporting transcription , 2012, BCS HCI.

[11]  Ana Iglesias,et al.  New Communication Technologies for Inclusive Education in and outside the Classroom , 2013 .

[12]  J. Paul Robinson,et al.  Using speech recognition for real-time captioning and lecture transcription in the classroom , 2013, IEEE Transactions on Learning Technologies.

[13]  Walter S. Lasecki,et al.  A readability evaluation of real-time crowd captions in the classroom , 2012, ASSETS '12.

[14]  Hiroaki Nanjo,et al.  Evaluation of Speech Balloon Captions for Auditory Information Support in Small Meetings , 2010 .

[15]  Liu Zhili,et al.  A study and application of speech recognition technology in primary and secondary school for deaf/hard of hearing students , 2010 .

[16]  Walter S. Lasecki,et al.  Online Sequence Alignment for Real-Time Audio Transcription by Non-Experts , 2012, AAAI.

[17]  Sara H. Basson,et al.  Accessibility, transcription, and access everywhere , 2005, IBM Syst. J..

[18]  Ira R. Forman,et al.  Using ASR for Transcription of Teleconferences in IM Systems , 2009, HCI.

[19]  Walter S. Lasecki,et al.  Online quality control for real-time crowd captioning , 2012, ASSETS '12.

[20]  Walter S. Lasecki,et al.  Adaptive time windows for real-time crowd captioning , 2013, CHI Extended Abstracts.

[21]  Richard E. Ladner,et al.  Hearing Impairments , 2008, Web Accessibility.

[22]  Tara Matthews,et al.  Scribe4Me: Evaluating a Mobile Sound Transcription Tool for the Deaf , 2006, UbiComp.

[23]  Ursula Faber,et al.  Requirements Engineering A Good Practice Guide , 2016 .

[24]  Wu xiao fen,et al.  Using speech recognition technology to support education for deaf students , 2010, 2010 2nd IEEE International Conference on Information Management and Engineering.

[25]  Seyed Ghorshi,et al.  Combining Augmented Reality and Speech Technologies to Help Deaf and Hard of Hearing People , 2012, 2012 14th Symposium on Virtual and Augmented Reality.

[26]  Mike Wald,et al.  Universal access to communication and learning: the role of automatic speech recognition , 2008, Universal Access in the Information Society.

[27]  I. Stewart,et al.  The application of voice recognition technology to the development and presentation of complex engineering terminology to hearing impaired students , 2003 .

[28]  Mike Wald.  Important New Enhancements to Inclusive Learning Using Recorded Lectures , 2012, ICCHP.

[29]  M. Marschark,et al.  Benefits of sign language interpreting and text alternatives for deaf students' classroom learning. , 2006, Journal of deaf studies and deaf education.

[30]  Walter S. Lasecki,et al.  Warping time for more effective real-time crowdsourcing , 2013, CHI.

[31]  Mike Wald.  Developing Assistive Technology to Enhance Learning for all Students , 2009 .

[32]  Mike Wald.  Captioning Multiple Speakers Using Speech Recognition to Assist Disabled People , 2008, ICCHP.

[33]  R. Punch,et al.  Inclusion in postsecondary institutions with small numbers of deaf and hard-of-hearing students: highlights and challenges. , 2014, Journal of deaf studies and deaf education.

[34]  Walter S. Lasecki,et al.  Real-time captioning by non-experts with legion scribe , 2013, ASSETS.

[35]  Daniela Tibaldi,et al.  Net4Voice - New Technologies for voice-converting in barrier-free learning environment , 2008, FECS.

[36]  Hanseok Ko,et al.  Dialogue enabling speech-to-text user assistive agent with auditory perceptual beamforming for hearing-impaired , 2013, 2013 IEEE International Conference on Consumer Electronics (ICCE).

[37]  Dzmitry Aliakseyeu,et al.  Transcription Table: Text Support During Meetings , 2005, INTERACT.

[38]  Thomas Way,et al.  Inclusion of deaf students in computer science classes using real-time speech transcription , 2007, ITiCSE '07.

[39]  Javier Jimenez,et al.  Tablet PC and Head Mounted Display for live closed captioning in education , 2011, 2011 IEEE International Conference on Consumer Electronics (ICCE).

[40]  David A. van Leeuwen,et al.  Attuning speech-enabled interfaces to user and context for inclusive design: technology, methodology and practice , 2009, Universal Access in the Information Society.

[41]  Mike Wald,et al.  Enhancing the Usability of Real-Time Speech Recognition Captioning Through Personalised Displays and Real-Time Multiple Speaker Editing and Annotation , 2007, HCI.

[42]  M. Wald.  Using Automatic Speech Recognition to Enhance Education for All Students: Turning a Vision into Reality , 2005, Proceedings Frontiers in Education 35th Annual Conference.

[43]  Li Ye,et al.  Using speech recognition technology to come true Liberated Learning for deaf students , 2009, 2009 4th International Conference on Computer Science & Education.