Speaker Diarization - Extracting speaker embeddings for labels from files with multiple speakers from MSDD models
**Is your feature request related to a problem? Please describe.**

One problem I come across often is, that I can't verify already known speakers from other files, since inference only yields labels for a **MSDD model** approach.
For example: I have file **A** with speakers Paul, Tom and Charlie and File **B** with speaker Bert, Charlie and Johann. To determine if **Charlie is in File A and B**, I have to get his speaker embedding. At the moment I have to infer speaker diarization on file A to do this, get the timestamps for Charlie, cut the file at the marks, stitch it together again and get the corresponding feature embedding which I can then compare to file B, by doing the same. However for a production setup I would need the embedding from the MSDD model, but from my understanding the MSDD model only produces a probability vector?

**Describe the solution you'd like**

A solution would be to extract the feature embeddings with some kind of method, after diarization and associate them with the labels. I found the get_cluster_avg_embs_model() method for MSDD models, but I am not sure how to use it and if it yields the correct results (to me its not clear which parameters to use here, since there are a lot of internal states in the model after diarization). So the question would, which parameter yields the best representation of a speaker to recognize him again?

