Comments (1)
As explained in the readme, "This project only shows how to generate speaker embeddings using pre-trained model for uis-rnn training in later." I suppose information on how to train the speaker embeddings can be found in this repo or this one (official VGG code). It was trained on openslr, VCTK and VoxCeleb datasets.
Concerning the pretrained UISRNN weights, I assume it was trained on the 4 speakers dataset available in this repo, but it'd be great to have a clear confirmation.
from speaker-diarization.
Related Issues (20)
- How to save the Plot/Animation/Video with Audio HOT 1
- Can not reprodcut the cluster result HOT 1
- Innacurate start and till time of slices attained HOT 2
- What is the exact version of tensorflow and Keras needed if I want to run the code? HOT 1
- Cuda Out Of Memory when invoking train.py HOT 3
- I want only 2 speakers as my output ,as my sample consists of only 2 speakers,what change in code should i do to achieve this
- Is there a way to fine tune the pre-trained model on another language data?
- How many utterances and iteration you use for pretrained uisrnn model
- Which version of Keras, Tensorflow and Pytorch are compatible? HOT 7
- Speaker-Diarization for 2 person conversation HOT 3
- How can I generate this training set file「./ghostvlad/training_data.npz」
- Diarization result varries as we run inference multiple time on same audio.
- what about your parameters of embeddings_per_second and overlap_rate consistent with your results in readme?
- how to get the label of rmdmy.wav to calculate the DER?
- Predicted labels doesn't match with Ground truth labels but the accuracy of test results is 0.8%
- Hello, can you provide the papers published on this model?
- How to generate a dynamic diagram to show
- spec_len = sr/hop_length/embedding_per_second
- 数据集
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from speaker-diarization.