Speaking Haptically: From Phonemes to Phrases With a Mobile Haptic Communication System

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.