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<p>Inspired by the auditory system’s capacity to process spatiotemporal sound patterns, voiceprint recognition plays a vital role in identity authentication and security. However, current platforms often face challenges of speech frequency and amplitude variability, hindering accurate feature extraction in noisy environments. To address these issues, a large-scale hybrid metal-halide dynamic memristor (MHDM) featuring an engineered gradient-distributed architecture is developed for adaptive voiceprint recognition. The spontaneously graded metal-halide functional layer allows for precise modulation of Schottky barriers and redistribution of interface charges. This design achieves µs-scale response, enhances noise tolerance (over 20% improvement in signal-to-noise ratio), and enables kHz-scale dynamic signal processing. Experimental results demonstrate that the MHDM achieves a voiceprint recognition accuracy of 99.3%, maintaining high performance at 93.2% even in realistic background noise. These findings demonstrate the system’s potential for secure and efficient voiceprint recognition, combining scalability with robust performance in noisy environments.</p>

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Gradient-distributed metal-halide dynamic memristors for adaptive and robust voiceprint recognition

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月19日

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  • He Shao,
  • Jianyu Ming,
  • Ruiheng Wang,
  • Wei Yang,
  • Xiang He,
  • Jintao Sun,
  • Benxin Liu,
  • Wen Li,
  • Li Gao,
  • You Meng,
  • Linghai Xie,
  • Johnny C. Ho,
  • Haifeng Ling,
  • Wei Huang

摘要

Inspired by the auditory system’s capacity to process spatiotemporal sound patterns, voiceprint recognition plays a vital role in identity authentication and security. However, current platforms often face challenges of speech frequency and amplitude variability, hindering accurate feature extraction in noisy environments. To address these issues, a large-scale hybrid metal-halide dynamic memristor (MHDM) featuring an engineered gradient-distributed architecture is developed for adaptive voiceprint recognition. The spontaneously graded metal-halide functional layer allows for precise modulation of Schottky barriers and redistribution of interface charges. This design achieves µs-scale response, enhances noise tolerance (over 20% improvement in signal-to-noise ratio), and enables kHz-scale dynamic signal processing. Experimental results demonstrate that the MHDM achieves a voiceprint recognition accuracy of 99.3%, maintaining high performance at 93.2% even in realistic background noise. These findings demonstrate the system’s potential for secure and efficient voiceprint recognition, combining scalability with robust performance in noisy environments.