随笔分类 -  语音增强(SE)

Speech Enhancement
摘要:论文地址:语义听觉:用双耳可听器编程声学场景 论文代码:https://semantichearing.cs.washington.edu/ 引用格式:Veluri B, Itani M, Chan J, et al. Semantic Hearing: Programming Acoustic S 阅读全文
posted @ 2023-12-06 11:19 凌逆战 阅读(1225) 评论(0) 推荐(1)
摘要:论文地址:微型循环U-Net实时降噪和去混响 论文代码: https://github.com/YangangCao/TRUNet https://github.com/Okrio/tinyrecurrentunet 引用格式:Choi H S, Park S, Lee J H, et al. Re 阅读全文
posted @ 2023-06-26 15:27 凌逆战 阅读(2306) 评论(2) 推荐(1)
摘要:论文地址:THLNet: 用于单耳语音增强的两级异构轻量级网络 代码:https://github.com/dangf15/THLNet 引用格式:Dang F, Hu Q, Zhang P. THLNet: two-stage heterogeneous lightweight network f 阅读全文
posted @ 2023-03-21 14:18 凌逆战 阅读(2255) 评论(2) 推荐(7)
摘要:论文地址:相位感知深度语音增强:这完全取决于帧长 论文代码:https://github.com/CarmiShimon/Phase-Aware-Deep-Speech-Enhancement 引用格式:Peer T, Gerkmann T. Phase-aware deep speech enha 阅读全文
posted @ 2023-02-08 20:05 凌逆战 阅读(1652) 评论(7) 推荐(4)
摘要:博客地址:凌逆战 (转载请注明出处) 论文地址:PercepNet+: 用于实时语音增强的相位和信噪比感知 PercepNet 引用格式: Ge X, Han J, Long Y, et al. PercepNet+: A Phase and SNR Aware PercepNet for Real 阅读全文
posted @ 2023-02-05 17:03 凌逆战 阅读(1978) 评论(0) 推荐(1)
摘要:论文地址:TEA-PSE: 用于ICASSP 2022 DNS挑战赛的Tencent-ethereal-audio-lab 个性化语音增强系统 论文代码: 引用格式:Ju Y, Rao W, Yan X, et al. TEA-PSE: Tencent-ethereal-audio-lab pers 阅读全文
posted @ 2023-02-03 16:06 凌逆战 阅读(2180) 评论(0) 推荐(2)
摘要:论文地址:TEA-PSE 2.0:用于实时个性化语音增强的子带网络 引用:Ju Y, Zhang S, Rao W, et al. Tea-pse 2.0: Sub-band network for real-time personalized speech enhancement[C]//2022 阅读全文
posted @ 2023-02-02 10:47 凌逆战 阅读(1178) 评论(0) 推荐(2)
摘要:论文地址:带轴向注意的多尺度时域频率卷积网络语音增强 论文代码:https://github.com/echocatzh/MTFAA-Net 引用:Zhang G, Yu L, Wang C, et al. Multi-scale temporal frequency convolutional n 阅读全文
posted @ 2022-12-09 09:41 凌逆战 阅读(2395) 评论(0) 推荐(1)
摘要:博客地址:凌逆战 论文地址:DeepFilternet2: 面向嵌入式设备的全波段音频实时语音增强 论文代码:https://github.com/Rikorose/DeepFilterNet 引用格式:Schröter H, Rosenkranz T, Maier A. DeepFilterNet 阅读全文
posted @ 2022-11-16 11:59 凌逆战 阅读(3478) 评论(2) 推荐(1)
摘要:论文地址:一种新的基于循环神经网络的远场语音通信实时噪声抑制算法 引用格式:Chen B, Zhou Y, Ma Y, et al. A New Real-Time Noise Suppression Algorithm for Far-Field Speech Communication Base 阅读全文
posted @ 2022-08-26 17:38 凌逆战 阅读(2142) 评论(0) 推荐(2)
摘要:论文地址:基于分层递归神经网络的嵌入式设备轻量化在线降噪 引用格式:Schröter H, Rosenkranz T, Zobel P, et al. Lightweight Online Noise Reduction on Embedded Devices using Hierarchical 阅读全文
posted @ 2022-08-16 21:41 凌逆战 阅读(1236) 评论(0) 推荐(0)
摘要:论文地址:延迟约束的语音增强基音估计 引用格式:Schröter H, Rosenkranz T, Escalante-B A N, et al. LACOPE: Latency-Constrained Pitch Estimation for Speech Enhancement[C]//Inte 阅读全文
posted @ 2022-08-07 21:37 凌逆战 阅读(797) 评论(0) 推荐(3)
摘要:论文地址:单耳语音增强的时频注意 引用格式:Zhang Q, Song Q, Ni Z, et al. Time-Frequency Attention for Monaural Speech Enhancement[C]//ICASSP 2022-2022 IEEE International C 阅读全文
posted @ 2022-08-04 11:29 凌逆战 阅读(1817) 评论(4) 推荐(3)
摘要:论文地址:TinyLSTMs:助听器的高效神经语音增强 音频地址:https://github.com/Bose/efficient-neural-speech-enhancement 引用格式:Fedorov I,Stamenovic M,Jensen C,et al. TinyLSTMs:Eff 阅读全文
posted @ 2022-04-18 12:00 凌逆战 阅读(1203) 评论(0) 推荐(1)
摘要:论文地址:深度噪声抑制模型的性能优化 引用格式:Chee J, Braun S, Gopal V, et al. Performance optimizations on deep noise suppression models[J]. arXiv preprint arXiv:2110.0437 阅读全文
posted @ 2022-04-09 23:11 凌逆战 阅读(1508) 评论(0) 推荐(1)
摘要:论文地址:面向基于深度学习的语音增强模型压缩 论文代码:没开源,鼓励大家去向作者要呀,作者是中国人,在语音增强领域 深耕多年 引用格式:Tan K, Wang D L. Towards model compression for deep learning based speech enhancem 阅读全文
posted @ 2022-04-08 10:58 凌逆战 阅读(1334) 评论(0) 推荐(0)
摘要:论文地址:DCCRN:用于相位感知语音增强的深度复杂卷积循环网络 论文代码:https://paperswithcode.com/paper/dccrn-deep-complex-convolution-recurrent-1 引用:Hu Y,Liu Y,Lv S,et al. DCCRN: Dee 阅读全文
posted @ 2022-03-09 15:23 凌逆战 阅读(3138) 评论(5) 推荐(7)
摘要:论文地址:双路信号变换LSTM网络的实时噪声抑制 论文代码:https://github.com/breizhn/DTLN 引用格式:Westhausen N L, Meyer B T. Dual-signal transformation LSTM network for real-time no 阅读全文
posted @ 2022-03-07 11:12 凌逆战 阅读(3077) 评论(4) 推荐(1)
摘要:论文地址:PACDNN:一种用于语音增强的相位感知复合深度神经网络 相似代码:https://github.com/phpstorm1/SE-FCN 引用格式:Hasannezhad M,Yu H,Zhu W P,et al. PACDNN: A phase-aware composite deep 阅读全文
posted @ 2022-02-15 15:39 凌逆战 阅读(1971) 评论(0) 推荐(3)
摘要:博客作者:凌逆战 论文地址:DeepFilterNet:基于深度滤波器的全频带音频低复杂度语音增强框架 论文代码:https://github.com/Rikorose/DeepFilterNet 引用:Schröter H, Rosenkranz T, Maier A. DeepFilterNet 阅读全文
posted @ 2022-01-20 21:21 凌逆战 阅读(4816) 评论(5) 推荐(5)