Tap to Sign: Towards using American Sign Language for
Text Entry on Smartphones
Saad Hassan[1], Abraham Glasser[2], Max Shengelia[3], Thad Starner[4], Sean Forbes[5], Nathan Qualls[5], Sam S. Sepah[4]
[1] Tulane University, [2] Gallaudet University
[3] Rochester Institute of Technology, [4] Google, [5] Deaf Professional Artist Network
Motivation
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Motivation
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Tap to Sign Text Entry Emulation
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Similar to how speech is used with the Assistant on Android currently.
Push to Sign Text Entry Emulation
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Similar to early “push-to-talk” speech recognition and walkie-talkies.
Recognition is easier because each word is isolated.
Tap to Sign: Towards using American Sign Language for
Text Entry on Smartphones
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Part 1
Part 2
Part 3
Training Required in a Fingerspelling Text Entry Interface
Is Fingerspelling Faster and more Preferred vs. Virtual Keyboard?
Smartphone Signing vs. Fingerspelling vs. Virtual Keyboard for Commanding a Mobile Assistant
Experimental Study
12 Deaf Participants
9 Females, 3 Males
Average Age: 33.6
RQ1: How much training is required to reach expertise in a fingerspelling text entry interface?
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Findings: Learning Curve
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Mackenzie-Soukoreff phrase set: all 500 phrases repeated twice
Tap to Sign: Towards using American Sign Language for
Text Entry on Smartphones
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Part 1
Part 2
Part 3
Training Required in a Fingerspelling Text Entry Interface
Is Fingerspelling Faster and more Preferred vs. Virtual Keyboard?
Smartphone Signing vs. Fingerspelling vs. Virtual Keyboard for Commanding a Mobile Assistant
Experimental Study
12 Deaf Participants
1-hour Study
Split into 3 sessions
RQ2 Are the Tap to Sign and Push to Sign fingerspelling prototypes faster and more preferred for text entry versus a virtual keyboard for Deaf users trained to expertise with the fingerspelling interface?
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Virtual Keyboard Prototype
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Findings: Text Entry Speeds over Time
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Findings: Text Entry Speeds over Time
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Condition | Speed (WPM) | Corrected Error Rate | Uncorrected Error Rate | Bandwidth | Throughput |
Tap to Sign | 39.3 (10.1) | 4.97% (6.19%) | 0.761% (1.23%) | 94.0% (3.52%)* | 13.2 (3.28) |
Push to Sign | 42.5 (11.3)* | 4.02% (4.27%) | 0.866% (1.13%) | 95.4% (3.40%)* | 14.2 (3.78)* |
Virtual Keyboard | 31.9 (10.1) | 6.46% (2.26%) | 0.770% (0.372%) | 88.3% (3.60%) | 10.9 (3.45) |
* indicates statistical significance over virtual keyboard
Findings: NASA TLX Questionnaire
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Findings: NASA TLX Questionnaire
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Findings: NASA TLX Questionnaire
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Findings: Subjective Feedback Questionnaire
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Half preferred Tap to Sign; half virtual keyboard
Tap to Sign: Towards using American Sign Language for
Text Entry on Smartphones
18
Part 1
Part 2
Part 3
Training Required in a Fingerspelling Text Entry Interface
Is Fingerspelling Faster and more Preferred vs. Virtual Keyboard?
Smartphone Signing vs. Fingerspelling vs. Virtual Keyboard for Commanding a Mobile Assistant
In-the-Wild Study
12 Deaf and Hard of Hearing Participants
RQ3: In a walk-up usability evaluation, do Deaf users prefer fingerspelling and/or smartphone- signing for text entry over typing on a virtual smartphone keyboard to command an emulated virtual assistant?
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Smartphone Signing Emulated Mobile Assistant
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Fingerspelling Emulated Mobile Assistant
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Virtual Keyboard Emulated Mobile Assistant
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Findings: Naturalness and Subjective Preference
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Findings: Subjective Feedback Questionnaire
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Condition | System Usability Scale | "User-friendliness" Score | Net Promoter Score |
Smartphone Signing | 75.8 (13.7) | 6.17 (1.03) | 83.3% |
Fingerspelling Only | 63.5 (16.9) | 4.75 (2.30) | 0% |
Virtual Keyboard | 79.8 (11.9) | 6.10 (0.994) | 100% |
Findings: Qualitative
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Category | Use-case |
Navigation | Navigating to an address (P2, P3, P6), Viewing traffic (P11), Restaurants (P9, P11), Ride-sharing services (P9), Food-ordering services |
Communication | Communication with others (P1), Messages (P7), Email (P8) |
Information | Color of a flag (P4), Weather (P6, P7, P8, P10), News (P7), Technology release (P7), Recipes (P9), Gas Prices (P12), Deaf Events (P12) |
Device Control | Smartphone commands (P5), Temperature control (P5), Home information, e.g. lights on, doors locked (P5), Open Apps (P12), Record (P10) |
Personal Use | Appointments (P6, P7), Calendar (P6), Reminders (P6), Calendar (P6, P7), Productivity stats (P6), Reservations (P7), Tasks (P7), Paying Bills (P7), Movie releases (P7), Flights (P7), Timezones (P7), Health (P7), Pandemic (P7), Scriptures (P7), Documents (P8), Grocery List (P9) |
Findings: Qualitative
“I would use this everyday. I hope this could be ready today."
“It is a fantastic resource, even when I am moving or traveling"
“Will it pan to follow them, if they set it down?"
“while its dark, if you’re in bed"
“Can it read from a distance? or from up really close?"
ASL drops words [Signs a, the, and is]. It is hard to not sign when told to fingerspell. English grammar causes contrived signing and English word order.”
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Excitement
Feedback
Concerns
Summary and Takeaway
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Kaggle Fingerspelling Dataset
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>3 million fingerspelled characters
>100 Deaf signers
Thank You
Saad Hassan (saadhassan@tulane.edu)
Abraham Glasser (abraham.glasser@gallaudet.edu)
Max Shengelia (mas5627@rit.edu)
Thad Starner (thadstarner@google.com)
Sean Forbes (sean@dpan.tv)
Nathan Qualls (nathan@dpan.tv)
Sam S. Sepah (sepah@google.com)
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Tap to Sign: Towards using American Sign Language for
Text Entry on Smartphones
Saad Hassan[1], Abraham Glasser[2], Max Shengelia[3], Thad Starner[4], Sean Forbes[5], Nathan Qualls[5], Sam S. Sepah[4]
[1] Tulane University, [2] Gallaudet University
[3] Rochester Institute of Technology, [4] Google, [5] Deaf Professional Artist Network