Pinned Repositories
AudioClassification-Pytorch
The Pytorch implementation of sound classification supports EcapaTdnn, PANNS, TDNN, Res2Net, ResNetSE and other models, as well as a variety of preprocessing methods.
Beamforming-for-speech-enhancement
simple delaysum, MVDR and CGMM-MVDR
CGMM-MVDR
Implementation of the CGMM-MVDR beamforming (for python version please refer to https://github.com/funcwj/setk)
kaldi
mic_array
DOA, VAD and KWS for ReSpeaker Microphone Array
PPASR
基于PaddlePaddle实现端到端中文语音识别，从入门到实战，超简单的入门案例，超实用的企业项目。支持当前最流行的DeepSpeech2、Conformer、Squeezeformer模型
speechFeatures
语音处理，声源定位中的一些基本特征
ssl_code
声源定位c代码
VoiceprintRecognition-Pytorch
This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the same time, this project also supports MelSpectrogram, Spectrogram data preprocessing methods
Pytorch-MobileFaceNet
Pytorch实现的人脸识别明细MobileFaceNet模型，在预测使用MTCNN检测人脸，然后使用MobileFaceNet模型识别。
dc-j's Repositories
dc-j/AudioClassification-Pytorch
The Pytorch implementation of sound classification supports EcapaTdnn, PANNS, TDNN, Res2Net, ResNetSE and other models, as well as a variety of preprocessing methods.
dc-j/Beamforming-for-speech-enhancement
simple delaysum, MVDR and CGMM-MVDR
dc-j/CGMM-MVDR
Implementation of the CGMM-MVDR beamforming (for python version please refer to https://github.com/funcwj/setk)
dc-j/kaldi
dc-j/mic_array
DOA, VAD and KWS for ReSpeaker Microphone Array
dc-j/PPASR
基于PaddlePaddle实现端到端中文语音识别，从入门到实战，超简单的入门案例，超实用的企业项目。支持当前最流行的DeepSpeech2、Conformer、Squeezeformer模型
dc-j/speechFeatures
语音处理，声源定位中的一些基本特征
dc-j/ssl_code
声源定位c代码
dc-j/VoiceprintRecognition-Pytorch
This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the same time, this project also supports MelSpectrogram, Spectrogram data preprocessing methods