基于结构化频谱压缩的低比特率安全语音通信在物联网辅助非地面网络中的应用
Structured Spectral Compression based Low-Bitrate Secure Speech Communications for Internet of Things assisted Non-Terrestrial Networks
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中文总结 AI 辅助
研究基于结构化频谱压缩的低比特率安全语音通信，通过波形分割、数据量化等编码，结合ARQ与前向纠错实现可靠传输，仿真表明该方法隐私保护强、时间复杂度低、内存需求少且编码率低。
中文摘要 AI 辅助
本文聚焦基于结构化频谱压缩的低比特率安全语音通信（LB-S2C2）。在发射端，通过基于波形分割和数据量化的压缩感知对语音信号的梅尔频谱矩阵进行编码，结合自动重传请求与前向纠错实现无线信道可靠传输。接收端恢复语音信号。仿真实验表明，语音重建字典矩阵与高阶矩阵稀疏化字典矩阵即便仅约0.1%的差异，都会导致语音恢复失败，意味着保护字典矩阵可实现安全传输。LB-S2C2隐私保护能力强，平均声纹相似度仅0.3，低于其他方案。其结构化语音编码时间复杂度仅O(n)，语音恢复方案仅需12位内存存储，优于传统算法。频谱压缩方法编码率仅3.9kbps，低于G.723的6.3kbps。
英文摘要
This paper focuses on the Low-Bitrate Secure Speech Communications based on the Structured Spectral Compression (LB-S2C2). Specifically, the Mel spectral matrix of the speech signal is first encoded at the transmitter side through compressive sensing based on waveform segmentation and data quantization. Then, the Automatic Repeat Request (ARQ) is combined with forward error correction to achieve reliable transmission of speech signals over wireless channels. Thirdly, the received signals are recovered as the speech at the receiver side. Finally, we conduct a series of simulation experiments for the performance evaluation of LB-S2C2. Our simulations reveal that the dictionary matrix used for the speech reconstruction is different from the one used for the high-order matrix sparsification by even only approximately 0.1%, and then the accurate speech recovery fails. It implies that the speech data can be securely transmitted when the dictionary matrix is preserved. More importantly, the LB-S2C2 exhibits a very high privacy protection capability with the average voiceprint similarity to be only 0.3, which is much lower than the 0.8 of the semantic speech communication scheme DeepSC-S, and even lower than the 0.33 of the latest speech communication scheme OFI-OFCNB. In addition, our simulations reveal that the proposed structured speech coding boasts a time complexity of merely O(n), and the proposed speech recovery scheme requires the 12-bit memory storage only, which outperforms the traditional encryption algorithms proposed for speech communications. In comparison with the conventional compression techniques, our spectral compression method renders the coding rate of only 3.9kbps, which is lower than the current lowest speech coding rate of 6.3kbps achieved by G.723.
