AI 中文总结
针对现有ANC技术难以抑制非平稳语音的问题，提出基于神经网络时间序列预测的主动语音抑制自适应滤波算法，实验验证其可提升降噪效果。
AI 中文摘要
本文提出一种基于语音信号时间序列预测的前馈主动噪声控制（ANC）方法。尽管现有ANC技术对平稳噪声抑制效果显著，但抑制高度非平稳的语音信号仍是一项极具挑战性的任务。我们提出一种主动语音抑制自适应滤波算法，该算法基于神经网络对未来信号的时间序列预测，线性控制滤波器的更新值由预测信号及当前、过去信号共同计算得出。数值实验表明，无论使用真实预测信号还是神经网络预测的信号，降噪效果均能得到提升。
英文摘要
A feedforward active noise control (ANC) method based on time-series prediction for speech signals is proposed. Although current ANC techniques are highly effective against stationary noise, suppressing highly non-stationary speech signals remains a challenging task. We propose an adaptive filtering algorithm for active speech suppression based on neural-network-based time-series prediction of future signals. The update value for the linear control filter is calculated based on the predicted signal, as well as the current and past signals. Numerical experiments indicated that the noise reduction can be improved in both cases: when using the true predicted signal and when using a signal predicted by neural networks.
CommentsAccepted to APSIPA Annual Summit and Conference 2026
