OK, thanks for the introduction.
Good morning.
I am [INAUDIBLE] from [INAUDIBLE]..
Today, I'm going to talk over my research project
about the text [INAUDIBLE] for smart glasses which
is complimentary [INAUDIBLE] gaze input
and touch [INAUDIBLE] modalities.
This work is conducted with my advisor [INAUDIBLE],,
and the title of the paper is gaze-assisted
typing for smart activists.
First of all, why smart glasses users will need efficient text
entry methods--
we expected that most of typing text for the smartphone users
also can be recasted to a smartphone users
such as chatting with a friend, searching information
on the web, and also entering a password authentication.
So how smart glasses users should have to enter text--
we first focused on the touch input modality
because touch input on the temple
is one of the widely used input methods for the smart glasses.
However, the temple on the glasses
are not a common form factor.
It has the oblong form factor.
And so [INAUDIBLE] any text entry method for it
is quite challenging.
Some researchers presented nice adaptations
of text [INAUDIBLE] method for this common form factor
[INAUDIBLE] touch pad.
One example is using unistrokes gestures.
[INAUDIBLE] designed 2016 [INAUDIBLE] stroke [INAUDIBLE]
just for corresponding 26 [INAUDIBLE]..
And another example is to two step touch [INAUDIBLE] input.
Because the touch input is too smart
to select the letter properly, Grossman [INAUDIBLE]
split the input stage into two stages
and presenting swipe [INAUDIBLE] and swipe [INAUDIBLE]
techniques as the two step touch typing method.
[INAUDIBLE] surely effective methods
on this kind of touch pad, but the limited space of the temple
makes touch gestures to be complex to use.
Considering that the problem is on the complexity
of the gestures, eye typing can be a possible alternative
[INAUDIBLE].
Popular eye typing methods is [INAUDIBLE] method.
To enter a Q with a [INAUDIBLE] method,
a user only has to look at the key for a while.
It is the more simple operation then the unistroke gestures
and the two step touch typing method.
Considering that we are in possession of the glasses,
eye gaze is also a promising input modality
for the smart glasses.
In fact, [INAUDIBLE] already exists such as [INAUDIBLE]
and [INAUDIBLE] which is high fidelity
mixed reality device have been announced to provide eye gazing
input modality.
So the eye typing message can be an alternative for the touch
typing on the template.
Eye typing is easy to use if the eye tracker will track
the user's eye very accurately.
However, considering both the display idea
of the smart glasses and the accuracy of eye tracker,
the answer is questionable.
The size of display will restrict the keyboard size
and consequently restrict type key size.
As a result, if the eye tracker is not
very accurate to select the small target,
users will be separated by our control.
And the second program is eye fatigue.
As you can see in the video, users
tend to not blink their eyes while doing eye typing.
And it caused eye fatigue.
So [INAUDIBLE] the problems on the touch typing
and eye typing, we present the gaze-assisted typing method.
It is a complementary combination
of touch typing and eye typing.
Gaze-assisted typing, so-called GAT,
is the kind of a two step input method.
First, a user has to select one of the [INAUDIBLE] keyboard
by looking at the key.
And second and lastly, the users should
have to enter one of the keys in the selection [INAUDIBLE]
keyboards by doing one of the corresponding touch input
gestures.
OK, let us see in step by step with our initial design.
Initial [INAUDIBLE] used the nine touch gestures
and the keyboard split into the three sub-keyboards.
First, user can select sub-keyboards by looking at it.
In this stage, the sub-keyboards simultaneously
responded to user's [INAUDIBLE].
Next, for example, if a user wants to enter the key C,
the user first looks at the sub keyboards.
And then to enter the key, user has t touch on the touch pad.
While the user's fingers is on the touch pad,
the sub keyboards do not respond to user's eye [INAUDIBLE]
position.
Due to this picture, user can relatively freely
move their eyes while conducting the touch gestures.
And next, the user has to conduct pattern [INAUDIBLE]
direction swipe gestures to enter
the C because the C is located on the bottom right
from the center.
[INAUDIBLE] in the sub-keyboards [INAUDIBLE]
to corresponding touch gestures based on each relative position
from the center position.
Finally, after user has touched the finger from the touch pad,
the case entered.
So we designed the GAT consistent with the following
goals--
more easy to use than touch only method and more [INAUDIBLE]
than eye only method and also less
eye fatigue than eye only method.
First, [INAUDIBLE] to use typing method-- we tested a 3D printed
[INAUDIBLE] to use.
The maximum number of touch gestures in our design
is nine, including four diagonal swipe gestures and two
vertical swipe gestures and two horizontal swipe
gestures and a touch gesture.
In case of diagonal swipe gestures,
it is known as hard to use on the temple because
of the narrow form vector.
In our panel study, also vertical surface [INAUDIBLE]
had to use as the same reason.
So we weighed the [INAUDIBLE] options
to eliminate those hard-to-use touch gestures first.
And next, towards [INAUDIBLE] durable from the eye tracker's
inaccuracy and also toward less eye fatigue in interface
than [INAUDIBLE] method.
We [INAUDIBLE] the number of split [INAUDIBLE]
sub-keyboards.
Due to the display size is limited,
the number of [INAUDIBLE] is directly
affected to effective target sizing of the eye selection
target.
And largely effective target size more error tuneable
than a small target sized one.
In [INAUDIBLE],, we assume that [INAUDIBLE] interface
may cause less eye fatigue because it required less
visual attention to the users.
In short, however, here is the trade-off between the options.
To use more [INAUDIBLE] gesture, you will [INAUDIBLE]
GAT3 is more [INAUDIBLE] and GAT9 is more easy to use
and two of the more [INAUDIBLE] interface [INAUDIBLE]
some less eye fatigue.
GAT3 is more effective.
So we conducted experiment one to figure out
which option is best.
Those three figures are the three options.
GAT3 consists of three sub-keyboards
and uses nine touch gestures.
And GAT6 consisted of six sub-keyboards
and used five touch gestures.
And GAT9 consisted nine sub-keyboards
and used three touch gestures.
We used-- we did [INAUDIBLE] design
to compare each of [INAUDIBLE] options
and also used it to memorize [INAUDIBLE] transcription tasks
with a commonly used place.
In our implementation, we use the Google glass
to use touch pad on the temple.
But this experiment was conducted in a remote eye
tracking environment rather than lab environment
in order to use properly reliable eye tracker.
Consequently, glass [INAUDIBLE] were also
provided on the remote monitor.
As a result, however, there were no significant differences
across the three options in terms of speed and accuracy.
Try to figure out why the text entries [INAUDIBLE]
were not very different across the options.
We decomposed the key input time into four parts.
And finally, we found that sub-keyboard selection time
and touch [INAUDIBLE] time which are the T1 and T4 canceled
each other out.
So obviously, [INAUDIBLE] to show
similar text entry [INAUDIBLE].
At the conclusion of experiment one,
even if the performance were that different to each other,
most qualitative measures indicated that w86 is best.
But in this experiment, we pressed the keys
in a priori order because GAT6 is
hard to make the layout as a familiar one similar
to the QWERTY layout.
So considering layout familiarity
will affect usability.
We didn't select the GAT6 as the best one.
Excluding GAT6, second [INAUDIBLE] option [INAUDIBLE]
GAT9.
So we concluded that GAT9 is best in this experiment.
And finally, to prove the effectiveness
with [INAUDIBLE] compared to touch only method and eye
only method, we conducted the experiment two.
Richard [INAUDIBLE] is a touch [INAUDIBLE] competitor
and just [INAUDIBLE] time method as the eye [INAUDIBLE]
competitor because [INAUDIBLE] surely be present other typing
method for each categories.
And also, we used the same test [INAUDIBLE]
as in experiment one.
And so this is the demonstration video
for the GAT9 in this experiment.
As you may know, user first selects
one of the nine sub-keyboards with he user's eyes.
Then the selected sub-keyboard is highlighted
with blue borderline.
Finally, user can enter a key with three touch gestures.
And then this is the video for the swipe [INAUDIBLE]..
Due to time constraints, I can explain detail,
but [INAUDIBLE] user has to select
one of the nine sub-keyboards with three touch gestures.
But instead, the user must have to distinguish
the three distinguishing touch [INAUDIBLE] region
on the temple.
And so the users can select one of the nine sub-keyboards,
then select one of the three keys with [INAUDIBLE] gestures
and [INAUDIBLE] gestures after selecting the region.
And finally, this is the adjustable dwell time method.
[INAUDIBLE] dwelling method, a user
only has to look at the keys for a while
over the preset [INAUDIBLE] time.
The user also can adjust the preset [INAUDIBLE] time
as [INAUDIBLE] after every end of the trial
as you can see in the video.
And [INAUDIBLE] in experiment two,
we used wearable head-worn display which also
has [INAUDIBLE] eye tracker.
So the [INAUDIBLE] contents were provided
on the head-worn display.
And we also used Google Glass to use the touch pad.
As a result of the experiment, GAT
was fastest over each [INAUDIBLE] text entry method.
After the 24 trials, GAT can reach 11 WPM,
and compared to touch only method, it is 29% faster.
And compared to eye only method, it is 25% faster method.
Yeah.
Next, about the runability--
we ask the participant to rate how the given technique
is [INAUDIBLE] in five point [INAUDIBLE] scale.
And their figure is cumulated [INAUDIBLE] the question.
Red color means very negative rating
and blue color means very positive ratings.
And the annotated numbers indicate [INAUDIBLE] values.
As a result, [INAUDIBLE] was lightest as more easy
to run then touch only method.
And next [INAUDIBLE] preference, GAT was more preferred
than eye only method.
And for the eye fatigue, GAT was more [INAUDIBLE]
than touch only method, unfortunately,
but less fatiguing than eye only method.
So it meets our goal maybe.
Finally, for the eyes only method,
4 out of 12 participants severely [INAUDIBLE]
inaccuracy of eye tracker.
But for the GAT, [INAUDIBLE] support by inaccuracy.
So we concluded that GAT was more [INAUDIBLE]
than eye only method.
So it's the conclusion and contribution.
Our contribution is presenting the [INAUDIBLE] typing,
and show we can make synergy [INAUDIBLE]
in terms of performance and qualitative measures.
GAT was fastest compared to the monomodal typing method,
and GAT was more easy to run than touch only method.
And also, GAT was preferred than eyes only method
and less [INAUDIBLE] than eyes only method.
And GAT was more [INAUDIBLE] than the eye only method.
However, it's the main limitation.
The limitation is our experiments
were conducted in the simulated environment.
So in our next work, we will investigate the environment
of validity utilizing eye tracker [INAUDIBLE]
smart glasses to [INAUDIBLE] the limitation.
Thank you.
[INAUDIBLE]
Thanks for your work.
Jake Weber from the University of Washington.
I'm a little concerned about seeing speed results
with no error rates.
I think that we are--
Oh.
--at a state of affairs where that should never happen.
So I might have missed it, but I think
around slide 41, the results from the first experiment--
Yeah.
--were just speed.
Did you force people to have perfect accuracy,
and that's why you're only reporting speed?
Otherwise, I don't know how to evaluate speed without errors.
Oh, sorry.
I can't [INAUDIBLE] about the last words.
[INAUDIBLE]
Did you-- what were the error rates, the text entry error
rates, that you saw in the results
for the first experiment?
Yeah, sorry.
Actually, we measure the error rate
for the possible experiment, but it
goes over the time constraint.
I [INAUDIBLE] the results because there
are no significant difference in error rate.
But in case of the experiment two,
GAT shows lowest error rate compared to the other method
but not significant in statistically.
One more quick question.
I think he was first.
Have you thought about applying this
to a word-based method instead of a letter-based method?
Sorry, sorry.
What method?
Words instead of letters.
Words, words--
Whole words, selecting whole words--
Yeah.
--instead of selecting letter by letter.
Ah, letter-wise-- my approach is letter-wise input.
And so your question is using to the [INAUDIBLE] test
input, yeah, right?
Maybe?
I would-- [INAUDIBLE]
OK.
Maybe you can discuss offline--=
sure.
--just in the interest of time.
Oh, yeah.
[INAUDIBLE] Yeah.
Sorry about that.
We need to--
OK, let's give him a big hand again.