Umair Khan

I-Vector Transformation Using K-Nearest Neighbors for Speaker Verification

Probabilistic Linear Discriminant Analysis (PLDA) is the most efficient backend for i-vectors. However, it requires labeled background data which can be difficult to access in practice. Unlike PLDA, cosine scoring avoids speaker-labels at the cost of degrading the performance. In this work, we propo…