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    Area of Science:

    • Human-Computer Interaction
    • Assistive Technology
    • Haptic Communication

    Background:

    • Traditional speech-based assistive technologies can be limited.
    • Developing intuitive interfaces for non-auditory communication is crucial.
    • WhatsHap explores alternative sensory pathways for information transfer.

    Purpose of the Study:

    • To evaluate the WhatsHap system for delivering speech via forearm vibrations.
    • To assess user learning curves and generalization of haptic phoneme recognition.
    • To determine the effectiveness of WhatsHap in supporting communicative tasks.

    Main Methods:

    • Participants trained on a 24-haptic phoneme vocabulary and word formation.
    • Word identification accuracy measured with user-controlled and fixed intervals.
    • Task completion rates assessed for communicative interactions.

    Main Results:

    • Users achieved 65% accuracy in identifying untrained words after ~4.2 hours of training.
    • Word identification reached 59% with fixed intervals.
    • Participants successfully completed 88% of communicative tasks.

    Conclusions:

    • WhatsHap demonstrates feasibility for speech-to-vibration communication.
    • Minimal training enables effective haptic word recognition and task completion.
    • Potential for naturalistic communication applications using vibrotactile feedback.