Closed ky941122 closed 4 years ago
Check out calc_same_diff_likelihood_ratio()
in plda/plda/model.py. The function returns a ratio in log space, so you can essentially classify the two sets of data as being generated by the same or different categories by using a threshold of 0.
Credit goes to @seandickert for implementing it. I will try to update the demo if I get a this weekend. Closing the issue for now.
Got it! Thanks for replying.
I want to use this repo to do a speaker recognition experiment. In my case, I have numbers of i-vectors from different speakers in training set. After I training the model, I want to use it to classify some vectors from unknonwn speakers belonging some other classes which are not in training set, and each class already has some labeled vectors. Just like the situation in the paper Sec-3.1 said. But I can only find the way to classify these vectors to the same classes in training set by using .predict() method. So how can I fix this new classes problem.