Speaker-Diarization | speaker diarization by uis-rnn and speaker embedding | Machine Learning library

Speaker-Diarization is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Keras, Neural Network applications. Speaker-Diarization has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

The confusion matrix of 4 persons utterances is as below. Thanks to the authors of VGG, they are kind enough to provide the code and pre-trained model. Their paper can refer to UTTERANCE-LEVEL AGGREGATION FOR SPEAKER RECOGNITION IN THE WILD It's a novel idea that combines netvlad/ghostvlad which popularly used in image recognition to speaker recognition, the state-of-the-art in the past was i-vector based, which depended on the GMM model and pLDA. About VGG speaker model, I have re-implemented in tensorflow, ghostvlad-speaker and corresponding pretrained model. This project only shows how to generate speaker embeddings using pre-trained model for uis-rnn training in later. The training project link to VGG-Speaker-Recognition.