A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Analysis of Complementary Information Sources in the Speaker Embeddings Framework
2018
Interspeech 2018
Deep neural network (DNN)-based speaker embeddings have resulted in new, state-of-the-art text-independent speaker recognition technology. However, very limited effort has been made to understand DNN speaker embeddings. In this study, our aim is analyzing the behavior of the speaker recognition systems based on speaker embeddings toward different front-end features, including the standard Mel frequency cepstral coefficients (MFCC), as well as power normalized cepstral coefficients (PNCC), and
doi:10.21437/interspeech.2018-1102
dblp:conf/interspeech/NandwanaMCHL18
fatcat:s4xhvarvkfcjnkwsu6gvkwuzjy