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Lessons from an Individual’s Language to Improve a AAC System

Learn how to calculate scan steps, measure layout efficiency, and improve alphabet boards for switch scanning in AAC systems.

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Lessons from an Individual’s Language to Improve a AAC System

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  1. Lessons from an Individual’s Language to Improve a AAC System Network, Learn, Share Will Wade (Ace Centre) Heidi Koester (President, Koester Performance Research)with thanks to Samantha McNeilly (Ace Centre)

  2. Learning Objectives • Be able to calculate at least three scan steps required for a switch scanning layout • Identify two differences in theoretical speed gains across 4 different scanning layouts for AAC • Describe four pros and cons of language sampling to improve an alphabet board for switch scanning

  3. Speaker Disclosures • Speaker has no Financial or Non-Financial Relationships to disclose.

  4. What we are going to cover • Background : low-tech communication for literate individuals • Background: Scan steps and frequency of letters. Measuring the efficiency of a layout • The question: Our client – David. Story so far • Aims: The questions raised • Results • Discussion – the key lessons learnt from this work for AAC • Implications for high-tech • Warning: Data is subject to change pending peer review. • Full data, embedded references and updated info will be online at https://acecentre.org.uk/project/switch-scanning-frequency-analysis/

  5. Who are we? • Ace Centre • A charity providing information, training and assessment services to children and adults across the UK and beyond • See approximately 20% of English Population in NHS Contract for AAC • Approximately 450 individuals per year seen for AAC assessments • A number of resources online and traininghttp://acecentre.org.uk • http://aacinfo.email

  6. Part 1. Low-tech (no-tech!)

  7. Scanning – a primer • Scanning is a technique which can be used on high-tech and low-tech • In low-tech systems the human is the computer! • There are different ways of making scanning easier and more efficient • For this presentation we are focusing on the alphabet (i.e., letters – not words or phrases)

  8. Linear..

  9. Linear..

  10. Linear..

  11. Row-Column ROW 1

  12. Row-Column ROW 2

  13. Row-Column ROW 2

  14. Row-Column ROW 2

  15. Steps.. The efficiency of any letter layout for can be measured by scan steps where each individual “step” or element in the scan is counted.  Linear: A (1), B (2), C (3) The number you start at is arbitrary. You must compare all charts with the same method Row Column:

  16. Letter frequencies Take any book and keep a count of every letter When you finish the book put them in order of frequency (highest to lowest) Do it for a second book and, if the book is around the same context (and language) you will find a similar frequency order Now do this for all the books in the world!

  17. Google books data Letter frequencies of all the books scanned by Google up to 2012 3,563,505,777,820 letters in total Top 12 = about 80% Top 8 = about 65% Letter B is only 1.48%. In a typical linear list of scanning this is the second item. English Letter Frequency Counts: Mayzner Revisited or ETAOIN SRHLDCU, Peter Norvig 2016

  18. An aside.. It’s not new! Job case for printing press. Note E bigger and B is small Items of high frequency positionedcentrally Morse code – based on common letters in shortest codes Note that different languages have a different common frequency order In small corpuses – context is key Image source: job case: http://www.briarpress.org/typecase/about, morse: http://www.sarcnet.org/activities/activity_morse_code.html

  19. And back to scanning.. Due to this factor a number of authors have suggested providing letters in a “frequency” order to speed up access For any type of scanning, map the letters of highest frequency to lowest by scan steps So for Linear scanning this may be: E, T, A, O, I, N, S, R, H, L, D, C, U, M, F, P, G, W, Y, B, V, K, X, J, Q, Z

  20. Row-Column Because several positions have the same scan steps, you can put a number of letters in different positions. It’s one of the reasons why there is no standard frequency layout. From ScanningWizard.com This chart has a space. This is the most common character. Numbers & Punctuation start around the 21st most common characters – 1.24% BUT: In many low-tech charts a space is omitted or (anecdotally) – rarely used

  21. Defining efficiency of a layout A number of techniques. A very simple metric is to look at: Sum (Scan Steps x Frequency) Frequency = no. of occurrences of n character/ Total no. of characters Provides a relative weighting of the importance of each letter in a chart To define you need to calculate alongside a corpus. What corpus you use is key. (Remember: Context and Language are key). SxF

  22. 2. David

  23. David In 2010 David had a brain stem stroke Very minor flexion of right thumb – but tiring and hard to maintain Can look up and has some flexion of the jaw No vocalisations Provided a chart in hospital post stroke for communication All carers efficient at using chart and have mostly learnt it so no longer need it in front of them All words recorded in notebooks

  24. David In 2010 David had a brain stem stroke Very minor flexion of right thumb – but tiring and hard to maintain Can look up and has some flexion of the jaw No vocalisations Provided a chart in hospital post stroke for communication All carers efficient at using chart and have mostly learnt it so no longer need it in front of them All words recorded in notebooks

  25. Video https://www.youtube.com/watch?v=hcOr8xROo1U Note how space is predicted by saying the word Numbers are either spelt or they are linear scanned when required

  26. Why the layout? EATSROIN. Clearly from a frequency list BUT – being delivered in a row-column order rather than a linear order. What can we learn from David? What should we provide for high-tech?

  27. Aims Is this EATSROIN layout which is being presented in a row-column order the most efficient layout for his communication needs? (We will define this as his “EATSROIN” layout going forward) What layout should we be offering to clients when they are using partner assisted scanning? Do we need to analyse data from all of our clients to give them a suitable low-tech frequency layout? (i.e., is David’s language markedly different to others or from written texts?)

  28. Method David consulted and consent given to transcribe 3 months of speech. Aware that language would be analysed but not shared further than Ace Centre. Carers provided instruction to record as much as possible “We already do!” Asked to try and note predictions down e.g. “move a|rm” – rm predicted. Data then analysed (https://github.com/ACECentre/SwitchFrequencyAnalysis) Chart compared with other standard charts commonly used Predictions of time made

  29. Results

  30. Summary data

  31. Comparing David’s language with Google books?

  32. Reorganised layout for his language So reorganised a chart based on frequency of letters found in his 3 month corpus

  33. Time / efficiency estimations Time estimations are difficult. To do this you have to make assumptions. For our analysis: It is a 1 second scan rate (for rows and cells) All selections are made at the end of the second Every space/ confirmation takes 2 seconds, same as first item in the layout (Is it “Dog”?) David and his communication partners make no mistakes! i.e., no error correction No words are predicted. David spells everything in full Remember – we are only comparing against his own language over 3 months.

  34. Charts – with no space on chart

  35. Time savings estimations summary

  36. Key points His current layout could be improved by 17-19% by using a frequency layout for row-column scanning. Little differences seen between frequency distribution in Norvig data and David’s own language sample. Using an individual’s own language to base a communication system is showing only marginal benefits in this situation. EARDU – regular frequency layout should be as effective. Differences negligible. Note day to day conversation at home. In a university or business maybe different (But – difference in words – maybe not characters). If he was using a AEIOU or QWERTY chart it would be approximately 18% slower.

  37. Real timings? Comments https://www.youtube.com/watch?v=gyf4sQ28QQ0&feature=youtu.be Times are from “First line..” to selecting it. Note that when they get to ‘E’ of SHE they move on to ‘T’. If he gets it wrong THEN they ask is it correct? They assume it’s a whole word and only correct if he continues looking down Note ‘H’ and ‘N’. They made a mistake – the partner misread him –selected the line when he didn’t look up. Realised then started again Note also what happens on ‘E’. He looks up to select first row and continues looking up. Like a double hit. Some partners faster than others

  38. What if David chose the space on his chart? The findings are hard to compare with other published material because we are making space the same step count as the shortest step element in the chart– but including it in the vocabulary. In high-tech systems it is not easy to have a space as the same step count as the highest step count letter Let’s imagine he was selecting space on his chart. What would that do?

  39. Charts with space

  40. Time savings estimations (including Spaces)

  41. Differences Much larger improvements seen in the frequency organised charts (EARDU and DB frequency) – Approximately 30% vs 19%. Why the variation? Because space is such a highly frequent item - just having it in a different location is making a big difference

  42. Don’t compare with high-tech scanning The assumptions are key Space is critical. If it is on the chart – and some people may – then this should be considered.

  43. Conclusions so far Frequency layouts are efficient If an individual/AAC consultant does not feel comfortable with frequency charts take care before choosing QWERTY. ABCD is more efficient than QWERTY. Try and find a technique for eliminating the space – and any other characters Consider the nuances of smart partner communication

  44. Brainfingers David uses Brainfingers on a GridPad 13. (See Video) Uses a modified version of ”FastTalker” with his EATSROIN layout

  45. Scanning techniques 1 Switch Automatic scanning. Limited scanning options available Dasher with switches (https://www.youtube.com/watch?v=HzbBTIhd4TU) Nomon (https://www.youtube.com/watch?v=_VtLgdFGuU8) Huffman scanning (B. Roark, et al. (2015). `Huffman and Linear Scanning Methods with Statistical Language Models'. Augmentative and Alternative Communication 31(1):37-50.)

  46. Step Analysis

  47. Scan blocks

  48. References Damper, R.I. (1984) ‘Text composition by the physically disabled: a rate prediction model for scanning input’ Applied ergonomics 15(4), 289-296 H. H. Koester & S. P. Levine (1994). `Modeling the speed of text entry with a word prediction interface’. Rehabilitation Engineering, IEEE Transactions on 2(3):177-187 Jokinen, J.P.P., Sarcar, S., Oulasvirta, A., Silpasuwanchai, C., Wang, Z., and Reb, X. (2017) ‘Modelling Learning of New Keyboards’ [Online] available at: http://delivery.acm.org/10.1145/3030000/3025580/p4203-jokinen.pdf [accessed 16 June 2017] Lesher, G., Moulton, B. and Higginbotham, D.J. (1998) ‘Techniques for augmenting scanning communication’ Augmentative and Alternative Communication 14(2), 81-101 G. Lesher, et al. (2002). `Limits of human word prediction performance’. In Proceedings of the California State University Northridge Conference on Disability Technology MacKenzie, I.S. (2012) ‘Modeling Text Input for Single-switch Scanning’ Dept of Computer Science and Engineering, York University, Canada Norvig, P. (2012) ‘English Letter Frequency Counts: Mayzner Revised or ETAOIN SRHLDCU’ [Online] available at: http://norvig.com/mayzner.html [accessed 16 February 2017] Venkatagiri, H.S. (1999) ‘Efficient Keyboard layouts for Sequential Access in Augmentative and Alternative Communication’ AAC Alternative and Augmentative Communication 15, 126-134

  49. Thank you for Attending! • CEUs: Session Code: AAC-56 • More info at: https://www.atia.org/conference/education-program/ceus/ • Visit the information desk for more information on CEUs. ASHA and ACVREP forms must be submitted before departing the conference. AOTA and IACET forms can be submitted online. • ATIA is an Approved Provider for IACET and AOTA CEUs. Please note there is a $15 fee for AOTA CEUs. • Session Evaluation • Help us improve the quality of our conference by completing your session evaluation form in the mobile app. • Handouts • Handouts are available at: www.atia.org/orlandohandouts • Handout link remains live for 3 months after the conference ends.

  50. Data and full details at: https://acecentre.org.uk/project/switch-scanning-frequency-analysis/With thanks to Heidi Koester for reviewing data and analysis Network, Learn, Share Will Wade wwade@acecentre.org.uk @acecentre

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