语音信号去混响(dereverberation)最新研究总结——附论文与代码

语音信号去混响是语音降噪的一种方法,本文现将至2020年7月经典的算法总结如下,按时间顺序排序。

算法目录

    • 1. Two-stage algorithm by DeLiang Wang's Group
      • 方法概述
      • 论文与代码
    • 2. About This Dereverberation Business: A Method for Extracting Reverberation from Audio Signals
      • 专利与代码:
    • 3. WPE
      • 论文与代码
    • 4. Exemplar-based sparse representations by Deepak Baby
      • 论文与代码:
    • 5. SPENDRED (SPeech ENhancement and DeREverberation by Doire)
      • 论文与代码:
    • 6. DNN_WPE
      • 论文与代码:

1. Two-stage algorithm by DeLiang Wang’s Group

方法概述

Inverse filter Arrangements
语音信号去混响(dereverberation)最新研究总结——附论文与代码_第1张图片
语音信号去混响(dereverberation)最新研究总结——附论文与代码_第2张图片

论文与代码

Mingyang Wu and DeLiang Wang, “A two-stage algorithm for one-microphone reverberant speech enhancement,” in IEEE Transactions on Audio, Speech, and Language Processing, vol. 14, no. 3, pp. 774-784, May 2006, doi: 10.1109/TSA.2005.858066.

Matlab 代码

2. About This Dereverberation Business: A Method for Extracting Reverberation from Audio Signals

专利与代码:

Soulodre, Gilbert A. 2010. “About this dereverberation business: A method for extracting reverberation from audio signals.” In Audio Engineering Society Convention 129. Audio Engineering Society.

Matlab 代码

3. WPE

论文与代码

Yoshioka, Takuya, and Tomohiro Nakatani. “Generalization of multi-channel linear prediction methods for blind MIMO impulse response shortening.” IEEE Transactions on Audio, Speech, and Language Processing 20.10 (2012): 2707-2720.

Python 代码

4. Exemplar-based sparse representations by Deepak Baby

论文与代码:

Deepak Baby and Hugo Van hamme. Supervised Speech Dereverberation in Noisy Environments using Exemplar-based Sparse Representations. In Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on, Shanghai, China, March 2016.

Matlab 代码

5. SPENDRED (SPeech ENhancement and DeREverberation by Doire)

论文与代码:

C. S. J. Doire, D. M. Brookes, P. A. Naylor, C. M. Hicks, D. Betts, M. A. Dmour, and S. H. Jensen. Single-channel online enhancement of speech corrupted by reverberation and noise. IEEE Trans. Audio, Speech, Language Processing, 25 (3): 572-587, Mar. 2017. doi: 10.1109/TASLP.2016.2641904.

Matlab 代码

6. DNN_WPE

论文与代码:

Kinoshita, Keisuke et al. “Neural Network-Based Spectrum Estimation for Online WPE Dereverberation.” INTERSPEECH (2017).

Python 代码

你可能感兴趣的:(音频学习笔记,算法,语音信号处理,语音混响,去混响)