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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.

Nature Communications

|March 11, 2025

Summary

This summary is machine-generated.

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.