FM1288用于对语音进行音频降噪和回声消除，同时具有增益调节和均衡控制功能。此压缩包包含FM1288数据手册、配置指导和原理图；还配有调试软件

针对高风险背景下的混沌时间序列区间预测问题,首次将回声状态网络与一致性预测框架相结合,提出基于两者的混沌时间序列区间预测算法.该算法将回声状态网络的拟合能力与一致性预测区间的可靠性相结合,使得最终的预测区间包含被预测值的频率或概率可以被显著性水平参数所控制,即预测区间具有极高的可信度.同时,由于使用岭回归学习回声状态网络的输出权重,使得算法在学习阶段对样本的留一交叉估计可以被快速地计算,极大地缩短了一致性预测的学习时间.理论分析表明,所提出算法的时间复杂度等价于原始回声状态网络算法的时间复杂度,即算法具有较快的计算速度.实验表明,所提出算法能够较精确地控制预测的错误率,对噪声具有鲁棒性,且预测区间比基于高斯过程的预测区间更加准确地刻画了被预测值的波动范围.

The echo canceller is based on the MDF algorithm described in: J. S. Soo, K. K. Pang Multidelay block frequency adaptive filter, IEEE Trans. Acoust. Speech Signal Process., Vol. ASSP-38, No. 2, February 1990. We use the Alternatively Updated MDF (AUMDF) variant. Robustness to double-talk is achieved using a variable learning rate as described in: Valin, J.-M., On Adjusting the Learning Rate in Frequency Domain Echo Cancellation With Double-Talk. IEEE Transactions on Audio, Speech and Language Processing, Vol. 15, No. 3, pp. 1030-1034, 2007. http://people.xiph.org/~jm/papers/valin_taslp2006.pdf There is no explicit double-talk detection, but a continuous variation in the learning rate based on residual echo, double-talk and background noise. About the fixed-point version: All the signals are represented with 16-bit words. The filter weights are represented with 32-bit words, but only the top 16 bits are used in most cases. The lower 16 bits are completely unreliable (due to the fact that the update is done only on the top bits), but help in the adaptation -- probably by removing a "threshold effect" due to quantization (rounding going to zero) when the gradient is small. Another kludge that seems to work good: when performing the weight update, we only move half the way toward the "goal" this seems to reduce the effect of quantization noise in the update phase. This can be seen as applying a gradient descent on a "soft constraint" instead of having a hard constraint.

1. 音频回声消除分析工具，非常好用。 2. 工具使用非常方便，一个简单的命令就可以了。

这是一个Windows平台下利用ffmpeg推流和拉流的示例，使用了微软的回声抑制功能，效果很不错。

回声法语音信息隐藏内涵数据集以及源码，主要对语音信息加密的研究

python的speexdsp 要求 wig 编译工具链 Python libspeexdsp-dev 建造 有两种构建程序包的方法。 使用setup.py sudo apt install libspeexdsp-dev git clone https://github.com/xiongyihui/speexdsp-python.git cd speexdsp-python python setup.py install 使用Makefile git clone https://github.com/xiongyihui/speexdsp-python.git cd speexdsp-python/src make 开始吧 """Acoustic Echo Cancellation for wav files.""" import wave import sys from s

webrtcd的aec模块的matlab实现，包括了频域NMLS滤波以及后期的非线性处理部分。可以得到较好的回声消除效果。

非常好用的回声抵消算法代码实现

FM1288数据手册 配置指导 原理图 还有回声消除寄存器配置代码