This paper extends our previous work on feature transformationbased support vector machines for speaker recognition by proposing a joint MAP adaptation of feature transformation (...
Speaker recognition using support vector machines (SVMs) with features derived from generative models has been shown to perform well. Typically, a universal background model (UBM)...
One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speake...
In recent years, adaptation techniques have been given special focus in speaker recognition tasks, mainly targeting speaker and session variation disentangling under the Maximum a...
This paper presents a non-parallel training algorithm for voice conversion based on feature transform Gaussian mixture model (FTGMM), which is a mixture model of joint density spa...