TiltText: Using Tilt for Text Input to Mobile Phones Daniel Wigdor & Ravin Balakrishnan.

25
TiltText: Using Tilt for Text Input to Mobile Phones Daniel Wigdor & Ravin Balakrishnan

Transcript of TiltText: Using Tilt for Text Input to Mobile Phones Daniel Wigdor & Ravin Balakrishnan.

TiltText: Using Tilt for Text Input to Mobile Phones

Daniel Wigdor & Ravin Balakrishnan

2

Text Messaging

• Estimated 500,000,000,000 text messages in 2003 worldwide

• More popular outside North America

3

Ambiguity

• Pressing “2” : {2,a,b,c,A,B,C}

4

Solutions

• MultiTap• Language-based disambiguation

• T9• Letterwise• Wordwise

• Alternate Layouts:

5

MultiTap: ~2.1 KSPC

e.g.: {6,6,6,>,6,6} = “on”

6

T9: ~1.2 KSPC

e.g.: {6,6} = “on”, “no”, “mo”,…

7

T9: Problems• Ambiguity persists

• Inconsistent

• Eyes-free operation impossible

• Only English-Like text

• No numerals

• Real “texting” impossible(“b4”,”btw”,”lol”,”rotflmao”…)

8

What’s best?

• Low KSPC

• Eyes-free

• Non-language specific

9

Tilt as input

• Add a tilt sensor to device• inexpensive accelerometers• Hinckley et al. UIST’00

• Tilt for text input:• Sazawal et al. Unigesture MobileHCI ‘02• Partridge et al. TiltType UIST’02

• No formal evaluations

10

TiltText: 1 KSPC + Tilt Action

eg: {7} = …

P

Q

R

S

11

Tilt Detection: Key Tilt

• Difference between press & release

• Slow: 3 consecutive actions• keypress, tilt, key-release

• Pilot study: poor performance

12

Tilt Detection: Absolute

• Relative to a fixed origin

• Keypress & tilt actions concurrent

• Consecutive same-tilt: savings

• Consecutive opposite-tilt: extra cost

• High error-rate: “creeping posture”

13

Tilt Detection: Relative

• Most recent tilting gesture• floating origin

• Maintains advantages of Absolute tilt

• Saves work on consecutive same tilts & consecutive opposite tilts

• No “creeping posture”

14

Our Prototype

• Uses Absolute tilt•• Tilts from board via serial port

15

The Study

• Repeated-measures design10 participants2 techniques (MultiTap & TiltText)16 blocks of 20 phrases eachin 2 sessions

• Same phrases for both techniques• Technique order between participant• Measured time & accuracy• Participants told to correct mistakes

16

Results: Overall Speed• Overall, TiltText 16% faster (including error correction)

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

TiltText

MultiTap

Block

WPM

17

Power-law extrapolation

y = 7.6837x0.2134

R2 = 0.9263

y = 8.0297x0.1184

R2 = 0.8963

0

2

4

6

8

10

12

14

16

1 3 5 7 9 11 13 15 17 19 21 23 25

TiltTextMultiTap

WPM

Block

18

Results: Between Participant• Data from 1st technique seen by each participant • TiltText still faster

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

TiltText

MultiTap

Block

WPM

19

Results: Error Rate• TiltText error rate higher than MultiTap

Err

or

Rate

Perc

enta

ge

Block

0

2

4

6

8

10

12

14

16

18

20

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

TiltText

MultiTap

20

Error Rate: By Letter• Error rates much higher for some letters

Correct Letter

0

5

10

15

20

25

30

35

40

a b c d e f g h i j k l m n o p q r s t u v w x y z

Err

or

Rate

Perc

enta

ge

21

Error Rate: Tilt Direction• Direction significantly effects error rate• Creeping posture

0

5

10

15

20

25

30

35

40

Left Forward Right Back

Err

or

Rate

Perc

enta

ge

Correct Tilt Direction

22

Conclusions

• Implemented TiltText• Three distinct approaches for tilt• Formal study conducted• TiltText faster despite errors

23

Future Work

• Theoretical TiltText speed• KSPC is not the whole story

• Implement relative-tilt system• Deeper analysis of error causes• Longer study• Optimizing letter/key assignments

24

Acknowledgements

• Michael McGuffin• Richard Watson • DGP Lab members• Study participants• Microsoft Research

25