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中文核心期刊

语义引导的水下带噪语音通信

Semantic-guided underwater noisy speech communication

  • 摘要: 针对狭窄带宽的多径水声信道和信源噪声干扰导致的退化语音, 提出了一种语义引导的水下带噪语音通信系统, 实现了噪声环境下高效鲁棒的语音通信。首先, 通过引入语音去噪网络降低了信源噪声的影响。系统通过传输语音的语义信息, 实现了语音信号的极限压缩。针对信道噪声对数据的损伤, 使用语义纠错模块在接收端对退化的语义特征进纠错, 从而提高重建语音的可理解性。此外, 结合多阶段训练策略的退化知情模型进一步增强所提方法在水声信道中的鲁棒性和泛化性。最后, 在语音重建过程中使用多感受野−挤压激励融合模块以捕获语义特征中的全局语义信息, 优化重建语音的可理解性。仿真实验结果表明, 该方法在极低码率压缩的情况下, 在复杂的噪声环境和不同的水声信道条件中, 具有良好的重建性能。

     

    Abstract: To address degraded speech caused by narrow-bandwidth multipath underwater acoustic channels and source noise interference, this paper proposes a semantic-guided underwater noisy speech communication system, achieving efficient and robust speech communication in noisy environments. First, a speech-denoising network is introduced to reduce the impact of source noise. The system transmits the semantic information of speech, enabling extreme compression of the speech signal. In response to the damage caused by channel noise to the data, a semantic correction module is proposed to correct the degraded semantic features at the receiver, thereby improving the intelligibility of the reconstructed speech. Furthermore, the degradation-informed model, combined with a multi-stage training strategy, further enhances the robustness and generalization of the proposed method in underwater acoustic channels. Finally, the proposed multi-receptive-field squeeze-and-excitation fusion module is employed in the speech reconstruction process to capture global semantic information within the semantic features, optimizing the intelligibility of the reconstructed speech. Simulation results demonstrate that the proposed method delivers excellent reconstruction performance under very low bit rate compression, in complex noise environments, and across various channel conditions.

     

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