ABSTRACT
Many people have problems with reading, which limits their ability to participate in society. This paper explores tools that make text more accessible. For this, we interviewed experts, who proposed tools for different stakeholders and scenarios. Important stakeholders of such tools are people with cognitive impairments and non-native readers. Frequently mentioned scenarios are public administration, the medical domain, and everyday life. The tools proposed by experts support stakeholders by improving how text is compressed, expanded, reviewed, and experienced. In a survey of stakeholders, we confirm that the scenarios are relevant and that the proposed tools appear helpful to them. We provide the Accessible Text Framework to help researchers understand how the different tools can be combined and discuss how individual tools can be implemented. The investigation shows that accessible text tools are an important HCI+AI challenge that a large number of people can benefit from.
- Basant Agarwal, Heri Ramampiaro, Helge Langseth, and Massimiliano Ruocco. 2018. A deep network model for paraphrase detection in short text messages. Information Processing & Management 54, 6 (2018), 922–937.Google ScholarCross Ref
- Suha S. Al-Thanyyan and Aqil M. Azmi. 2021. Automated Text Simplification: A Survey. ACM Comput. Surv. 54, 2, Article 43 (March 2021), 36 pages. https://doi.org/10.1145/3442695Google ScholarDigital Library
- Oliver Alonzo, Matthew Seita, Abraham Glasser, and Matt Huenerfauth. 2020. Automatic Text Simplification Tools for Deaf and Hard of Hearing Adults: Benefits of Lexical Simplification and Providing Users with Autonomy. Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376563Google ScholarDigital Library
- Fernando Alva-Manchego, Carolina Scarton, and Lucia Specia. 2020. Data-driven sentence simplification: Survey and benchmark. Computational Linguistics 46, 1 (2020), 135–187.Google ScholarDigital Library
- Oscar Alvarado, Hendrik Heuer, Vero Vanden Abeele, Andreas Breiter, and Katrien Verbert. 2020. Middle-Aged Video Consumers’ Beliefs About Algorithmic Recommendations on YouTube. Proc. ACM Hum.-Comput. Interact. 4, CSCW2, Article 121 (oct 2020), 24 pages. https://doi.org/10.1145/3415192Google ScholarDigital Library
- Karin Bendixen and Maria Benktzon. 2015. Design for All in Scandinavia – A strong concept. Applied Ergonomics 46 (2015), 248–257. https://doi.org/10.1016/j.apergo.2013.03.004 Special Issue: Inclusive Design.Google ScholarCross Ref
- Larwan Berke, Sushant Kafle, and Matt Huenerfauth. 2018. Methods for Evaluation of Imperfect Captioning Tools by Deaf or Hard-of-Hearing Users at Different Reading Literacy Levels. Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3173574.3173665Google ScholarDigital Library
- Jeffrey P Bigham and Patrick Carrington. 2018. Learning from the front: People with disabilities as early adopters of AI. In Proceedings of the 2018 Annual Conference of the Human Computer Interaction Consortium (HCIC).Google Scholar
- BIK für Alle. 2021. German Agencies for Easy Language. https://bik-fuer-alle.de/agenturen-fuer-leichte-sprache.htmlGoogle Scholar
- Stefan Bott, Horacio Saggion, and David Figueroa. 2012. A hybrid system for spanish text simplification. In Proceedings of the Third Workshop on Speech and Language Processing for Assistive Technologies. 75–84.Google ScholarDigital Library
- LouAnne E. Boyd, Alejandro Rangel, Helen Tomimbang, Andrea Conejo-Toledo, Kanika Patel, Monica Tentori, and Gillian R. Hayes. 2016. SayWAT: Augmenting Face-to-Face Conversations for Adults with Autism. Association for Computing Machinery, New York, NY, USA, 4872–4883. https://doi.org/10.1145/2858036.2858215Google ScholarDigital Library
- Erin L Brady, Yu Zhong, Meredith Ringel Morris, and Jeffrey P Bigham. 2013. Investigating the appropriateness of social network question asking as a resource for blind users. In Proceedings of the 2013 conference on Computer supported cooperative work. 1225–1236.Google ScholarDigital Library
- Danielle Bragg, Oscar Koller, Mary Bellard, Larwan Berke, Patrick Boudreault, Annelies Braffort, Naomi Caselli, Matt Huenerfauth, Hernisa Kacorri, Tessa Verhoef, 2019. Sign language recognition, generation, and translation: An interdisciplinary perspective. In The 21st international ACM SIGACCESS conference on computers and accessibility. 16–31.Google ScholarDigital Library
- Danielle Bragg, Oscar Koller, Naomi Caselli, and William Thies. 2020. Exploring collection of sign language datasets: Privacy, participation, and model performance. In The 22nd International ACM SIGACCESS Conference on Computers and Accessibility. 1–14.Google ScholarDigital Library
- Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative Research in Psychology 3, 2 (jan 2006), 77–101. https://doi.org/10.1191/1478088706qp063oaGoogle ScholarCross Ref
- Ursula Bredel and Christiane Maaß. 2016. Leichte Sprache: Theoretische Grundlagen? Orientierung für die Praxis. Bibliographisches Institut GmbH.Google Scholar
- Deutscher Bundestag. 2018. Gesetz zur Gleichstellung von Menschen mit Behinderungen (Behindertengleichstellungsgesetz–BGG).Google Scholar
- Elena Cabrio and Serena Villata. 2018. Five Years of Argument Mining: a Data-driven Analysis.. In IJCAI, Vol. 18. 5427–5433.Google Scholar
- R Chandrasekar and B Srinivas. 1997. Automatic induction of rules for text simplification. Knowledge-Based Systems 10, 3 (1997), 183–190. https://doi.org/10.1016/S0950-7051(97)00029-4Google ScholarDigital Library
- Esther Chiner, Marcos Gómez-Puerta, and María Cristina Cardona-Moltó. 2017. Internet use, risks and online behaviour: The view of internet users with intellectual disabilities and their caregivers. British Journal of Learning Disabilities 45, 3 (2017), 190–197. https://doi.org/10.1111/bld.12192 arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/bld.12192Google ScholarCross Ref
- Wendy Chisholm and Matt May. 2008. Universal design for web applications: Web applications that reach everyone. O’Reilly Media, Inc.Google Scholar
- Ryan Colin Gibson, Mark D. Dunlop, and Matt-Mouley Bouamrane. 2020. Lessons from expert focus groups on how to better support adults with mild intellectual disabilities to engage in co-design. In The 22nd International ACM SIGACCESS Conference on Computers and Accessibility. 1–12.Google ScholarDigital Library
- Juliet Corbin and Anselm Strauss. 2014. Basics of qualitative research: Techniques and procedures for developing grounded theory. Sage publications.Google Scholar
- Raymundo Cornejo, Robin Brewer, Caroline Edasis, and Anne Marie Piper. 2016. Vulnerability, sharing, and privacy: Analyzing art therapy for older adults with dementia. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. 1572–1583.Google ScholarDigital Library
- William Coster and David Kauchak. 2011. Simple English Wikipedia: a new text simplification task. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. 665–669.Google Scholar
- Anna Decker. 2003. Towards automatic grammatical simplification of swedish text. Stockholm University Department of Linguistics Computational Linguistics (2003).Google Scholar
- Siobhan Devlin and Gary Unthank. 2006. Helping Aphasic People Process Online Information. In Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility (Portland, Oregon, USA) (Assets ’06). Association for Computing Machinery, New York, NY, USA, 225–226. https://doi.org/10.1145/1168987.1169027Google ScholarDigital Library
- William B Dolan and Chris Brockett. 2005. Automatically constructing a corpus of sentential paraphrases. In Proceedings of the Third International Workshop on Paraphrasing (IWP2005).Google Scholar
- Elizabeth Ellcessor. 2010. Bridging disability divides: A critical history of web content accessibility through 2001. Information, Communication & Society 13, 3 (2010), 289–308.Google ScholarCross Ref
- Günes Erkan and Dragomir R Radev. 2004. Lexrank: Graph-based lexical centrality as salience in text summarization. Journal of artificial intelligence research 22 (2004), 457–479.Google ScholarCross Ref
- Jinjuan Feng, Jonathan Lazar, Libby Kumin, and Ant Ozok. 2010. Computer Usage by Children with Down Syndrome: Challenges and Future Research. ACM Trans. Access. Comput. 2, 3, Article 13 (mar 2010), 44 pages. https://doi.org/10.1145/1714458.1714460Google ScholarDigital Library
- Christopher Frauenberger. 2015. Disability and technology: A critical realist perspective. In Proceedings of the 17th International ACM SIGACCESS Conference on Computers & Accessibility. 89–96.Google ScholarDigital Library
- Regine M Gilbert. 2019. Inclusive Design for a Digital World: Designing with accessibility in mind. Springer.Google Scholar
- Itziar Gonzalez-Dios, María Jesús Aranzabe, Arantza Díaz de Ilarraza, and Haritz Salaberri. 2014. Simple or complex? assessing the readability of basque texts. In Proceedings of COLING 2014, the 25th international conference on computational linguistics: Technical papers. 334–344.Google Scholar
- Anke Grotlüschen and Klaus Buddeberg. 2020. LEO 2018: Leben mit geringer Literalität. wbv.Google Scholar
- Anke Grotlüschen, Klaus Buddeberg, Gregor Dutz, Lisanne Heilmann, and Christopher Stammer. 2020. Low literacy in Germany. Results from the second German literacy survey. European journal for Research on the Education and Learning of Adults 11, 1 (2020), 127–143.Google ScholarCross Ref
- Leonor GuimarãEs, Nuno Martins, Leonardo Pereira, Eliana Penedos-Santiago, and Daniel BrandãO. 2023. Interface Design Guidelines for Low Literature Users: A Literature Review. In Proceedings of the 2022 6th International Conference on Education and E-Learning (Yamanashi, Japan) (ICEEL ’22). Association for Computing Machinery, New York, NY, USA, 29–35. https://doi.org/10.1145/3578837.3578842Google ScholarDigital Library
- Birgit Hamp and Helmut Feldweg. 1997. Germanet-a lexical-semantic net for german. In Automatic information extraction and building of lexical semantic resources for NLP applications.Google Scholar
- Kotaro Hara and Shamsi T. Iqbal. 2015. Effect of Machine Translation in Interlingual Conversation: Lessons from a Formative Study. Association for Computing Machinery, New York, NY, USA, 3473–3482. https://doi.org/10.1145/2702123.2702407Google ScholarDigital Library
- Naeemul Hassan, Mohammad Yousuf, Md Mahfuzul Haque, Javier A. Suarez Rivas, and Md Khadimul Islam. 2019. Examining the Roles of Automation, Crowds and Professionals Towards Sustainable Fact-Checking. In Companion Proceedings of The 2019 World Wide Web Conference (San Francisco, USA) (WWW ’19). Association for Computing Machinery, New York, NY, USA, 1001–1006. https://doi.org/10.1145/3308560.3316734Google ScholarDigital Library
- Jonathan L Herlocker, Joseph A Konstan, and John Riedl. 2000. Explaining collaborative filtering recommendations. In Proceedings of the 2000 ACM conference on Computer supported cooperative work. 241–250.Google ScholarDigital Library
- Hendrik Heuer. 2020. Users & Machine Learning-based Curation Systems.Google Scholar
- Hendrik Heuer and Elena Leah Glassman. 2023. Accessible Text Tools: Where They Are Needed & What They Should Look Like. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI EA ’23). Association for Computing Machinery, New York, NY, USA, Article 20, 7 pages. https://doi.org/10.1145/3544549.3585749Google ScholarDigital Library
- Hendrik Heuer, Juliane Jarke, and Andreas Breiter. 2021. Machine learning in tutorials – Universal applicability, underinformed application, and other misconceptions. Big Data & Society 8, 1 (2021), 20539517211017593. https://doi.org/10.1177/20539517211017593 arXiv:https://doi.org/10.1177/20539517211017593Google ScholarCross Ref
- Harald Holone and Jo Herstad. 2013. Three Tensions in Participatory Design for Inclusion. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI ’13). Association for Computing Machinery, New York, NY, USA, 2903–2906. https://doi.org/10.1145/2470654.2481401Google ScholarDigital Library
- Hurraki contributors. 2021. Hurraki, Wörterbuch für Leichte Sprache. https://hurraki.de/wiki/Hauptseite. [Online; accessed 25-June-2021].Google Scholar
- Dietmar Jannach, Markus Zanker, Alexander Felfernig, and Gerhard Friedrich. 2010. Recommender systems: an introduction. Cambridge University Press.Google ScholarDigital Library
- Juliane Jarke. 2021. Co-creating Digital Public Services for an Ageing Society : Evidence for User-centric Design. Springer Nature. https://doi.org/10.1007/978-3-030-52873-7Google ScholarCross Ref
- Stefan Johansson. 2019. Design for participation and inclusion will follow: Disabled people and the digital society. Ph. D. Dissertation. KTH Royal Institute of Technology.Google Scholar
- Sushant Kafle and Matt Huenerfauth. 2019. Predicting the Understandability of Imperfect English Captions for People Who Are Deaf or Hard of Hearing. ACM Trans. Access. Comput. 12, 2, Article 7 (jun 2019), 32 pages. https://doi.org/10.1145/3325862Google ScholarDigital Library
- Katherine M. King. 2019. Can Google Translate Be Taught To Translate Literature? A Case for Humanists To Collaborate in the Future of Machine Translation. Translation Review 105, 1 (2019), 76–92. https://doi.org/10.1080/07374836.2019.1673268 arXiv:https://doi.org/10.1080/07374836.2019.1673268Google ScholarCross Ref
- David Klaper, Sarah Ebling, and Martin Volk. 2013. Building a German/simple German parallel corpus for automatic text simplification. (2013).Google Scholar
- Jumpei Kobayashi and Toshio Kawashima. 2019. Paragraph-Based Faded Text Facilitates Reading Comprehension. Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300392Google ScholarDigital Library
- Joseph A Konstan, Bradley N Miller, David Maltz, Jonathan L Herlocker, Lee R Gordon, and John Riedl. 1997. Grouplens: Applying collaborative filtering to usenet news. Commun. ACM 40, 3 (1997), 77–87.Google ScholarDigital Library
- Wojciech Kryściński, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019. Neural text summarization: A critical evaluation. arXiv preprint arXiv:1908.08960 (2019).Google Scholar
- Inghard Langer, Friedemann Schulz von Thun, and Reinhard Tausch. 2015. Sich verständlich ausdrücken. Aufl. München: reinhardt (2015).Google Scholar
- Daniel J. Liebling, Michal Lahav, Abigail Evans, Aaron Donsbach, Jess Holbrook, Boris Smus, and Lindsey Boran. 2020. Unmet Needs and Opportunities for Mobile Translation AI. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376261Google ScholarDigital Library
- Peng Liu, Xianghua Ding, and Ning Gu. 2016. “Helping Others Makes Me Happy” Social Interaction and Integration of People with Disabilities. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. 1596–1608.Google Scholar
- H. P. Luhn. 1958. The Automatic Creation of Literature Abstracts. IBM Journal of Research and Development 2, 2 (1958), 159–165. https://doi.org/10.1147/rd.22.0159Google ScholarDigital Library
- Christiane Maaß. 2019. Leichte Sprache. Das Regelbuch. Lit-Verlag, Münster. 184 pages. https://doi.org/10.25528/018Google ScholarCross Ref
- Christiane Maaß. 2020. Easy Language–Plain Language–Easy Language Plus: Balancing comprehensibility and acceptability. Frank & Timme.Google Scholar
- Kelly Mack, Emma McDonnell, Dhruv Jain, Lucy Lu Wang, Jon E. Froehlich, and Leah Findlater. 2021. What Do We Mean by “Accessibility Research”? A Literature Survey of Accessibility Papers in CHI and ASSETS from 1994 to 2019. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 371, 18 pages. https://doi.org/10.1145/3411764.3445412Google ScholarDigital Library
- Wendy E Mackay. 1990. Users and customizable software: A co-adaptive phenomenon. Ph. D. Dissertation. Massachusetts Institute of Technology.Google Scholar
- Abdullah Al Mahmud and Jean-Bernard Martens. 2015. Iterative Design and Field Trial of an Aphasia-Friendly Email Tool. ACM Trans. Access. Comput. 7, 4, Article 13 (nov 2015), 36 pages. https://doi.org/10.1145/2790305Google ScholarDigital Library
- Jennifer Mankoff, Gillian R Hayes, and Devva Kasnitz. 2010. Disability studies as a source of critical inquiry for the field of assistive technology. In Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility. 3–10.Google ScholarDigital Library
- Paulo R. A. Margarido, Thiago A. S. Pardo, Gabriel M. Antonio, Vinícius B. Fuentes, Rachel Aires, Sandra M. Aluísio, and Renata P. M. Fortes. 2008. Automatic Summarization for Text Simplification: Evaluating Text Understanding by Poor Readers. In Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web (Vila Velha, Espírito Santo, Brazil) (WebMedia ’08). Association for Computing Machinery, New York, NY, USA, 310–315. https://doi.org/10.1145/1809980.1810057Google ScholarDigital Library
- Kerstin Matausch and Birgit Peböck. 2010. Easyweb–a study how people with specific learning difficulties can be supported on using the internet. In International Conference on Computers for Handicapped Persons. Springer, 641–648.Google ScholarCross Ref
- Indrani Medhi, Somani Patnaik, Emma Brunskill, S.N. Nagasena Gautama, William Thies, and Kentaro Toyama. 2011. Designing Mobile Interfaces for Novice and Low-Literacy Users. ACM Trans. Comput.-Hum. Interact. 18, 1, Article 2 (may 2011), 28 pages. https://doi.org/10.1145/1959022.1959024Google ScholarDigital Library
- Rada Mihalcea and Paul Tarau. 2004. Textrank: Bringing order into text. In Proceedings of the 2004 conference on empirical methods in natural language processing. 404–411.Google Scholar
- Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013).Google Scholar
- George A Miller. 1995. WordNet: a lexical database for English. Commun. ACM 38, 11 (1995), 39–41.Google ScholarDigital Library
- Cosmin Munteanu, Heather Molyneaux, Julie Maitland, Daniel McDonald, Rock Leung, Joanna Lumsden, and Hélène Fournier. 2012. Tale of Two Studies: Challenges in Field Research with Low-Literacy Adult Learners in a Developed Country. In CHI ’12 Extended Abstracts on Human Factors in Computing Systems (Austin, Texas, USA) (CHI EA ’12). Association for Computing Machinery, New York, NY, USA, 489–504. https://doi.org/10.1145/2212776.2212825Google ScholarDigital Library
- Mansour Neubauer. 2019. Einfache Sprache: Grundregeln, Beispiele, Übungen: Schreiben und Sprechen in Einfacher Sprache. Author’s edition (2019).Google Scholar
- Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, and Liviu P Dinu. 2017. Exploring neural text simplification models. In Proceedings of the 55th annual meeting of the association for computational linguistics (volume 2: Short papers). 85–91.Google ScholarCross Ref
- OECD (Organisation for Economic Co-operation and Development). 2018. PISA 2018 results. https://www.oecd.org/pisa/publications/pisa-2018-results.htm# [Online; accessed 28-July-2021].Google Scholar
- OpenAI. 2021. Examples. https://beta.openai.comGoogle Scholar
- Oxford English Dictionary. 2021. accessible, adj.https://www.oed.com/view/Entry/1034?redirectedFrom=accessibleGoogle Scholar
- Gustavo H Paetzold and Lucia Specia. 2017. A survey on lexical simplification. Journal of Artificial Intelligence Research 60 (2017), 549–593.Google ScholarCross Ref
- Alexander M Rush, Sumit Chopra, and Jason Weston. 2015. A neural attention model for abstractive sentence summarization. arXiv preprint arXiv:1509.00685 (2015).Google Scholar
- Horacio Saggion. 2017. Automatic text simplification. Synthesis Lectures on Human Language Technologies 10, 1 (2017), 1–137.Google ScholarCross Ref
- Horacio Saggion, Sanja Štajner, Stefan Bott, Simon Mille, Luz Rello, and Biljana Drndarevic. 2015. Making It Simplext: Implementation and Evaluation of a Text Simplification System for Spanish. ACM Trans. Access. Comput. 6, 4, Article 14 (may 2015), 36 pages. https://doi.org/10.1145/2738046Google ScholarDigital Library
- Magnus Sahlgren. 2008. The distributional hypothesis. Italian Journal of Linguistics 20 (Jan. 2008).Google Scholar
- Matthew Shardlow. 2014. A survey of automated text simplification. International Journal of Advanced Computer Science and Applications 4, 1 (2014), 58–70.Google ScholarCross Ref
- Sumita Sharma, Saurabh Srivastava, Krishnaveni Achary, Blessin Varkey, Tomi Heimonen, Jaakko Samuli Hakulinen, Markku Turunen, and Nitendra Rajput. 2016. Promoting joint attention with computer supported collaboration in children with autism. In Proceedings of the 19th ACM conference on computer-supported cooperative work & social computing. 1560–1571.Google ScholarDigital Library
- Advaith Siddharthan. 2014. A survey of research on text simplification. ITL-International Journal of Applied Linguistics 165, 2 (2014), 259–298.Google ScholarCross Ref
- Gabriella Skitalinskaya, Jonas Klaff, and Henning Wachsmuth. 2021. Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics, Online, 1718–1729. https://doi.org/10.18653/v1/2021.eacl-main.147Google ScholarCross Ref
- Lucia Specia. 2010. Translating from complex to simplified sentences. In International Conference on Computational Processing of the Portuguese Language. Springer, 30–39.Google ScholarDigital Library
- Katta Spiel, Christopher Frauenberger, Os Keyes, and Geraldine Fitzpatrick. 2019. Agency of autistic children in technology research—A critical literature review. ACM Transactions on Computer-Human Interaction (TOCHI) 26, 6 (2019), 1–40.Google ScholarDigital Library
- Katta Spiel, Kathrin Gerling, Cynthia L Bennett, Emeline Brulé, Rua M Williams, Jennifer Rode, and Jennifer Mankoff. 2020. Nothing about us without us: Investigating the role of critical disability studies in hci. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. 1–8.Google ScholarDigital Library
- Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul Christiano. 2020. Learning to summarize from human feedback. arxiv:2009.01325 [cs.CL]Google Scholar
- Julia Suter, Sarah Ebling, and Martin Volk. 2016. Rule-based automatic text simplification for German. (2016).Google Scholar
- Juan-Manuel Torres-Moreno. 2014. Automatic text summarization. John Wiley & Sons.Google Scholar
- United Nations. 2006. Convention on the Rights of Persons with Disabilities. Treaty Series 2515 (Dec. 2006), 3.Google Scholar
- Sukrit Venkatagiri, Jacob Thebault-Spieker, Rachel Kohler, John Purviance, Rifat Sabbir Mansur, and Kurt Luther. 2019. GroundTruth: Augmenting Expert Image Geolocation with Crowdsourcing and Shared Representations. Proc. ACM Hum.-Comput. Interact. 3, CSCW, Article 107 (Nov. 2019), 30 pages. https://doi.org/10.1145/3359209Google ScholarDigital Library
- Henning Wachsmuth, Nona Naderi, Yufang Hou, Yonatan Bilu, Vinodkumar Prabhakaran, Tim Alberdingk Thijm, Graeme Hirst, and Benno Stein. 2017. Computational argumentation quality assessment in natural language. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. 176–187.Google ScholarCross Ref
- Willian M. Watanabe, Arnaldo Candido, Marcelo A. Amâncio, Matheus de Oliveira, Thiago A. S. Pardo, Renata P. M. Fortes, and Sandra M. Aluísio. 2010. Adapting Web Content for Low-Literacy Readers by Using Lexical Elaboration and Named Entities Labeling. In Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A) (Raleigh, North Carolina) (W4A ’10). Association for Computing Machinery, New York, NY, USA, Article 8, 9 pages. https://doi.org/10.1145/1805986.1805998Google ScholarDigital Library
- Willian Massami Watanabe, Arnaldo Candido Junior, Vinícius Rodriguez Uzêda, Renata Pontin de Mattos Fortes, Thiago Alexandre Salgueiro Pardo, and Sandra Maria Aluísio. 2009. Facilita: Reading Assistance for Low-Literacy Readers. In Proceedings of the 27th ACM International Conference on Design of Communication (Bloomington, Indiana, USA) (SIGDOC ’09). Association for Computing Machinery, New York, NY, USA, 29–36. https://doi.org/10.1145/1621995.1622002Google ScholarDigital Library
- Wikipedia contributors. 2021. Functional illiteracy — Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Functional_illiteracy&oldid=1021404558 [Online; accessed 28-May-2021].Google Scholar
- Wikipedia contributors. 2021. List of countries by literacy rate — Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=List_of_countries_by_literacy_rate&oldid=1021549466 [Online; accessed 27-May-2021].Google Scholar
- Wikipedia contributors. 2021. List of languages by total number of speakers — Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=List_of_languages_by_total_number_of_speakers&oldid=1033562179. [Online; accessed 21-July-2021].Google Scholar
- Kristian Woodsend and Mirella Lapata. 2011. WikiSimple: Automatic simplification of Wikipedia articles. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 25.Google ScholarCross Ref
- Sander Wubben, EJ Krahmer, and APJ van den Bosch. 2012. Sentence simplification by monolingual machine translation. (2012).Google Scholar
- Naomi Yamashita and Toru Ishida. 2006. Effects of Machine Translation on Collaborative Work. In Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work (Banff, Alberta, Canada) (CSCW ’06). Association for Computing Machinery, New York, NY, USA, 515–524. https://doi.org/10.1145/1180875.1180955Google ScholarDigital Library
- Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020. Pegasus: Pre-training with extracted gap-sentences for abstractive summarization. In International Conference on Machine Learning. PMLR, 11328–11339.Google Scholar
- Xingxing Zhang and Mirella Lapata. 2017. Sentence simplification with deep reinforcement learning. arXiv preprint arXiv:1703.10931 (2017).Google Scholar
- Kristin Alfredsson Ågren, Anette Kjellberg, and Helena Hemmingsson. 2020. Digital participation? Internet use among adolescents with and without intellectual disabilities: A comparative study. New Media & Society 22, 12 (2020), 2128–2145. https://doi.org/10.1177/1461444819888398 arXiv:https://doi.org/10.1177/1461444819888398Google ScholarCross Ref
Index Terms
- Accessible Text Tools for People with Cognitive Impairments and Non-Native Readers: Challenges and Opportunities
Recommendations
Accessible Text Tools: Where They Are Needed & What They Should Look Like
CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing SystemsMany people have problems with reading, which limits their ability to participate in society. This paper explores tools that make text more accessible. For this, we interviewed experts who proposed scenarios and tools. Frequently mentioned scenarios are ...
Smart Kitchens for People with Cognitive Impairments: A Qualitative Study of Design Requirements
CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing SystemsIndividuals with cognitive impairments currently leverage extensive human resources during their transitions from assisted living to independent living. In Western Europe, many government-supported volunteer organizations provide sheltered living ...
Accessible Touchscreen Technology for People with Visual Impairments: A Survey
Touchscreens have become a de facto standard of input for mobile devices as they most optimally use the limited input and output space that is imposed by their form factor. In recent years, people who are blind and visually impaired have been increasing ...
Comments