Feasibility Study of Real-Time Speech Detection and Characterization Using Millimeter-Wave Micro-Doppler Radar

Nati Steinmetz, Nezah Balal

Research output: Contribution to journalArticlepeer-review

Abstract

This study presents a novel approach to remote speech recognition using a millimeter-wave micro-Doppler radar system operating at 94 GHz. By detecting micro-Doppler speech-related vibrations, the system enables non-contact and privacy-preserving speech recognition. Initial experiments used a piezoelectric crystal to simulate vocal cord vibrations, followed by tests with actual human speech. Advanced signal processing techniques, including short-time Fourier transform (STFT), were used to generate spectrograms and reconstruct speech signals. The system demonstrated high accuracy, with cross-correlation analysis quantitatively confirming a strong correlation between radar-reconstructed and original audio signals. These results validate the effectiveness of detecting and characterizing speech-related vibrations without direct audio recording. The findings have significant implications for applications in noisy industrial environments, enabling robust voice interaction capabilities, as well as in healthcare diagnostics and assistive technologies, where contactless and privacy-preserving solutions are essential. Future research will explore diverse real-world scenarios and the integration of advanced signal processing and machine learning techniques to further enhance accuracy and robustness.

Original languageEnglish
Article number91
JournalRemote Sensing
Volume17
Issue number1
DOIs
StatePublished - Jan 2025

Keywords

  • assistive technologies
  • IoT
  • micro-doppler
  • millimeter-wave radar
  • privacy
  • remote speech recognition
  • voice control

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