17 citations · 18 across the 3 of their papers we have counts for
5 papers
Latent Class Model with Application to Speaker Diarization
Liang He, Xianhong Chen, Can Xu +3
In this paper, we apply a latent class model (LCM) to the task of speaker diarization. LCM is similar to Patrick Kenny's variational Bayes (VB) method in that it uses soft informat…
Large Margin Softmax Loss for Speaker Verification
Yi Liu, Liang He, Jia Liu
In neural network based speaker verification, speaker embedding is expected to be discriminative between speakers while the intra-speaker distance should remain small. A variety of…
Exploring a Unified Attention-Based Pooling Framework for Speaker Verification
Yi Liu, Liang He, Weiwei Liu +1
The pooling layer is an essential component in the neural network based speaker verification. Most of the current networks in speaker verification use average pooling to derive the…
Speaker Embedding Extraction with Phonetic Information
Yi Liu, Liang He, Jia Liu +1
Speaker embeddings achieve promising results on many speaker verification tasks. Phonetic information, as an important component of speech, is rarely considered in the extraction o…
Comparison of Multiple Features and Modeling Methods for Text-dependent Speaker Verification
Yi Liu, Liang He, Yao Tian +3
Text-dependent speaker verification is becoming popular in the speaker recognition society. However, the conventional i-vector framework which has been successful for speaker ident…