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Machine learning-assisted wearable sensing systems for speech recognition and interaction.

Tao Liu1, Mingyang Zhang1, Zhihao Li1

  • 1Key Laboratory of Optoelectronic Technology & Systems of Ministry of Education, International R & D Center of Micro-nano Systems and New Materials Technology, Chongqing University, Chongqing, 400044, China.

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|March 11, 2025
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Summary

A new skin-attached acoustic sensor (SAAS) captures vocal organ vibrations for clear voice recognition, even in noisy settings. This wearable technology achieves over 99% accuracy for human-machine interaction and voice control applications.

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Area of Science:

  • Wearable technology
  • Acoustic sensing
  • Human-computer interaction

Background:

  • Voice communication is vital but vulnerable to noise and environmental interference.
  • Existing methods for voice recognition struggle in challenging acoustic conditions.
  • Advanced sensors are needed for reliable speech capture and interaction.

Purpose of the Study:

  • To develop a wearable, wireless, flexible skin-attached acoustic sensor (SAAS) for robust voice recognition.
  • To enable human-machine interaction (HMI) in harsh acoustic environments.
  • To improve the accuracy and reliability of speech recognition systems.

Main Methods:

  • Utilized piezoelectric micromachined ultrasonic transducers (PMUTs) for high sensitivity and wide bandwidth sensing.
  • Employed flexible packaging for enhanced wearability and adaptability.
  • Integrated the sensor data with a Residual Network (ResNet) deep learning architecture for speech feature classification.

Main Results:

  • The SAAS system demonstrated high sensitivity (-198 dB) and a wide bandwidth (10 Hz-20 kHz).
  • Laryngeal speech feature classification accuracy exceeded 96% using the ResNet architecture.
  • The complete speech recognition system achieved 99.8% accuracy in recognizing everyday sentences.

Conclusions:

  • SAAS offers a viable solution for voice recognition and HMI in noisy environments.
  • The sensor system exhibits stable performance, ease of integration, and low cost.
  • SAAS has significant potential for applications in voice control, advanced HMI, and wearable electronics.