Skip to main content
SpringerLink
Log in

Augmentative and alternative communication: the future of text on the move

  • LONG PAPER
  • Published:
Universal Access in the Information Society Aims and scope Submit manuscript

Abstract

The methods currently available for text entry on small mobile devices exhibit poor performance in terms of input speed, which presents a potential barrier to acceptance and growth. This paper presents an analysis of mobile text entry indicating that the likely solution is a combination of the use of language modelling and careful interaction design and verification. The paper argues that research in augmentative and alternative communication (AAC) is highly relevant to the mobile text entry problem and vice versa, and offers the opportunity to research solutions that will be feasible to implement on future generations of mobile devices. In the design of the system presented in this paper, fewer input buttons, natural language processing (NLP) and multimodal inputs are techniques that have been evaluated and applied. Contrary to initial expectations, analysis and evaluation showed that usability and human factors often are more significant factors in performance than the efficiency of the input method. In the conducted study, simplifications of a text-to-talk system increased productivity by 15%. This provides a strong indication that the best way to increase text production rates in realistic scenarios is to strive for simplicity and clarity in the interaction and user interface, rather than opting for including every possible time-saving feature in the system. Empirical validations of potential simplifications are therefore advocated as a general design methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4.
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. The prices for sending SMS messages have been steadily dropping since the introduction of the GSM network. Some operators have introduced special plans that favor heavy use of SMS, in some cases allowing unlimited SMS use in return for a slightly higher price per minute for voice calls. Current prices for the Danish carrier CBB are EUR 0.02 per SMS as compared to EUR 0.10 per minute for voice calls.

  2. According to the Danish National IT and Telecom Agency statistical yearbook for 2003 (http://www.telestyrelsen.dk), the average rate of text messages sent was 2.2 per day per user in 2003. Preliminary data indicates that this figure is even higher for 2004.

  3. A theoretically promising alternative is Morse code. Morse code is designed for efficient communication at a low input. Unfortunately, Morse takes time to learn and is no longer a common skill. Furthermore, it is difficult to design software that gives meaningful visual feedback for Morse. In short, it is very hard—possibly inherently impossible—to design a Morse input system that conforms to the guidelines for high user performance (cf. Sect. 2.1) and usability (cf. Sect. 2.4). Additionally, it is difficult for a computer to interpret single-switch Morse input (which it would be necessary to use in the late stage of ALS, due to degrading motor function) reliably. One problem is determining the length of the dot (“dit”) and dash (“dah”) signals, and there is also a segmentation problem, that is, determining where one letter ends and the next letter starts. This could conceivably be handled by using more than one switch, but would make the system unusable for users in the later stages of ALS (cf. Table 3).

References

  1. Smoreda Z, Thomas F (2004) Use of SMS in Europe, analysis of data from EURESCOM P903 study “Cross-cultural attitudes to ICT in everyday life” performed October to December 2000, http://www.eurescom.de/∼ftproot/web-deliverables/public/P900-series/P903/sms_use/w1-sms.html, verified 10

  2. MacKenzie S, Zhang Shawn X (2001) An empirical investigation of the novice experience with soft keyboards. Behav Inform Technol 20:411–418

    Article  Google Scholar 

  3. James Christina L, Reischel Kelly M (2001) Text input for mobile devices: comparing model prediction to actual performance. SIGCHI’01 March 31–April 4, 2001, pp 365–371, Seattle, WA, USA

  4. Silfverberg Miika, MacKenzie, I Scott, Korhonen Panu (2000) Predicting text entry speed on mobile phones. In: Proceedings of the ACM conference on human factors in computing systems—CHI. ACM, New York, pp 9–16

  5. MacKenzie I Scott, Zhang S The immediate usability of Graffiti. In: Proceedings of graphics interface 97. Canadian Information Processing Society, Toronto, pp 129–137

  6. Soukoreff R William, MacKenzie Scott I (1995) Theoretical Upper and lower bounds on typing speed using a stylus and soft keyboard. Behav Inform Technol 14:370–379

    Article  Google Scholar 

  7. Zhai Shumin, Hunter Michael, Smith Barton A (2000) The metropolis keyboard—an exploration of quantitative techniques for virtual keyboard design. In: Proceedings of the ACM symposium on user interface software and technology (UIST 2000), November 5–8, San Diego, pp 119–128

  8. Matias, E, MacKenzie IS, Buxton (1993) W Half-QWERTY: a one-handed keyboard facilitating skill transfer from QWERTY. In: Proceedings of the ACM conference on human factors in computing systems—INTERCHI 93. ACM, New York, pp 88–94

  9. Jecker Diane (2004) Benchmark tests: speech recognition. PC Magazine, November 1999, http://web.archive.org/web/20020202235749/http://www.zdnet.com/products/stories/reviews/0,4161,2385302,00.html verified 10

  10. A. T. Kearney/Judge Institute of Management (2004) Mobinet Index # 4”, February 2002, http://www.atkearney.com/shared_res/pdf/Mobinet_4_S.pdf verified 10

  11. Bellman, T, MacKenzie IS (1998) A probabilistic character layout strategy for mobile text entry. In: Proceedings of graphics interface ’98. Canadian Information Processing Society, Toronto, pp 168–176

  12. Wikipedia (2004) http://www.wikipedia.com/wiki/Morse+code, verified 10

  13. International Telecommunication Union recommendation E.161, available from http://www.itu.int

  14. Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391

    Article  Google Scholar 

  15. Hick WE (1952) On the rate of gain of information. Quart J Exp Psychol 4:11–36

    Article  Google Scholar 

  16. Hyman R (1953) Stimulus information as a determinant of reaction time. J Exp Psychol 45:188–196

    Article  Google Scholar 

  17. Shannon CE (1951) Prediction and entropy of printed english. Bell Syst Tech J 30:50–64

    Google Scholar 

  18. Rosenfeld R (1996) A maximum entropy approach to adaptive statistical language modelling. Comput Speech Lang 10:187–288

    Article  Google Scholar 

  19. Tilbourg H (1988) An introduction to cryptology. Kluwer, Dordrecht

    Google Scholar 

  20. Ward David J (2004) Adaptive computer interfaces. Ph.D. thesis, Inference Group, Cavendish Laboratory, University of Cambridge, November 2001, http://www.inference.phy.cam.ac.uk/djw30/ verified 10

  21. Marcus Aaron (2001) Babyface design for mobile devices and the web. In: Proceedings, Vol. 2, human–computer interface internet. (HCII) conference, 5–10. New Orleans, LA, USA, Lawrence Erlbaum Associates, Mahwah, NJ USA, pp 514–518

  22. Gutowitz Howard (2004) Barriers to adoption of dictionary-based text-entry methods: a field study. Submitted to CHI2002, September 2001 http://www.eatoni.com/research/field-study.pdf verified 10

  23. Schneiderman Ben (1992) Designing the user interface: strategies for effective human–computer interaction. (2 edition), Addison-Wesley, Reading

    Google Scholar 

  24. Dvorak A, Merrick WL, Ford GC (1936) Typewriting behaviour. American Book Company, New York

    Google Scholar 

  25. Wiklund ME, Dumas JS, Hoffman LR (1987) Optimizing a portable terminal keyboard for combined one-handed and two-handed use. In: Proceedings of the human factors society—31st annual Meeting. Human Factors Society, Santa Monica, CA, pp 585–589

  26. Hansen Paulin J, Witzner Dan, Johansen Anders S (2001) Bringing gaze-based interaction back to basics. In: Proceedings of universal access in human–computer interaction (UAHCI). New Orleans, Louisiana

  27. User Evaluation dot Com (2004) http://web.archive.org/web/20020526082338/http://www.userevaluation.com/ Verified 15

  28. Krug Steve (2000) Don’t make me think. Que

  29. Jordan Patrick W (1999) An introduction to usability. Taylor & Francis, London

    Google Scholar 

  30. Kühn Michael, Garbe Jörn (2001) Predictive and highly ambiguous typing for a severely speech and motion impaired user. Universal access in human–computer interaction. In: Proceedings of UAHCI, New Orleans, August 5–10. Lawrence Erlbaum Associates, Mahwah (NJ)

  31. Miniotas Darius (2000) Application of fitts’ law to eye gaze interaction. CHI 2000 Extended Abstracts, ACM, New York, pp 339–340

  32. Carlberger, J (1997) Design and implementation of a probabilistic word prediction program; NADA report TRITA-NA-E9751, Swedish Royal Institute of Technology, Department of Numerical Analysis and Computer Science (NADA), 1997

  33. Darragh John J, Witten Ian H, James Mark J (1990) The reactive keyboard: a predictive typing aid. IEEE Comput 23(11):41–49

    Google Scholar 

  34. MacKenzie IS, Kober H, Smith D, Jones T, Skepner E (2001) LetterWise: prefix-based disambiguation for mobile text input. In: Proceedings of the ACM symposium on user interface software and technology—UIST 2001. ACM, New York, pp 111–120

  35. Rau H, Skiena SS (1996) Dialing for Documents: An Experiment in Information Theory. J Vis Lang Comput 7(1):79–95

    Article  Google Scholar 

  36. Klarlund, N, Riley M (2003) Word n-grams for cluster keyboards. In: Proceedings of the EACL ‘03 workshop on language modeling for text entry methods, Budapest, Hungary, March

  37. Lesher GW, Moulton BJ, Higginbotham DJ (1998) Optimal character arrangements for ambiguous keyboards (1998). IEEE Trans Rehabil Eng 6:415–423

    Article  Google Scholar 

  38. Johansen Anders S, Hansen John P, Dan Witzner Hansen, Kenji Itoh, Satoru Mashino (2003) Language technology in a predictive, restricted on-screen keyboard with ambiguous layout for severely disabled people. In: EACL 2003 workshop on language modeling for text entry methods, April 13, Budapest, Hungary

  39. Arnott JL, Javed MY (1992) Probabilistic character disambiguation for reduced keyboards using small text samples. Augment Altern Commun 8:215–223

    Article  Google Scholar 

  40. Hansen JP, Tørning K, Johansen AS, Itoh K, Aoki H (2004) Gaze typing compared with input by head and hand. In: Paper presented at the ACM symposium on eye tracking research and applications (ETRA) 2004, March 22–24, San Antonio, Texas, USA, pp 131 138. ACM, New York. Available: http://www.doi.acm.org/10.1145/968363.968389

  41. Majaranta, PI, MacKenzie, S, Aula A, Räihä K (2003) Auditory and visual feedback during eye typing. In: Extended abstracts of the ACM conference on human factors in computing systems, CHI 2003, New York, ACM, New York

  42. Majaranta PI, MacKenzie S, Räihä, K (2003) Using Motion to guide the focus of gaze during eye typing. Abstract proceedings of ECEM12, 20–24 August 2003, Dundee, Scotland

  43. GSM Association (2004) What is SMS? GSM World, http://www.gsmworld.com/technology/sms/intro.shtml, verified 15

  44. Batista E (2004) Hush-Hush Hooray, Says NYC. Wired News, http://www.wired.com/news/business/0,1367,54608,00.html, verified 15

  45. Monk A, Carroll J, Parker S, Blythe M (2004) Why are mobile phones annoying?. Behav Inform Technol 23(1):33–41

    Article  Google Scholar 

  46. Soukoreff RW, MacKenzie IS (2001) Measuring errors in text entry tasks: an application of the Levenshtein string distance statistic. In: Extended abstracts of the ACM conference on human factors in computing system, CHI 2001, ACM, New York, pp 319–320

  47. John BE, Kieras DE (1996) The GOMS family of user interface analysis techniques: comparison and contrast. ACM Trans Comput Hum Interact 3(4):320–351

    Article  Google Scholar 

  48. Katz SM (1987) Estimation of probabilities from sparse data for the language model component of a speech recognizer. IEEE Trans Acoust Speech Signal Process 35(3):400–401

    Article  Google Scholar 

  49. Wikipedia (2005) http://www.wikipedia.com/wiki/Wpm, verified 4

  50. Wikipedia (2005) http://www.wikipedia.com/wiki/Zipf%27s_law, verified 4

Download references

Acknowledgments

This work was supported by (1) Ministry of Science, Technology and Innovation, Denmark, (2) COGAIN Network of Excellence, IST EU 6. Research program (http://www.cogain.org) (3) The Nordic Academy for Advanced Study (NorFA).

Author information

Authors and Affiliations

  1. The IT University of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen S, Denmark

    Anders Sewerin Johansen & John Paulin Hansen

Authors
  1. Anders Sewerin Johansen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John Paulin Hansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anders Sewerin Johansen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Johansen, A.S., Hansen, J.P. Augmentative and alternative communication: the future of text on the move. Univ Access Inf Soc 5, 125–149 (2006). https://doi.org/10.1007/s10209-006-0033-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10209-006-0033-0

Keywords

Search

Navigation