Skip to content

Implementation of state of the art d-vector approach for speaker verification

Notifications You must be signed in to change notification settings

liusongxiang/speaker-verification-d-vector

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 

Repository files navigation

d-vector approach for Speaker Verification implemented in Keras

Reference for DNN: Variani, Ehsan, Xin Lei, Erik McDermott, Ignacio Lopez Moreno, and Javier Gonzalez-Dominguez. "Deep neural networks for small footprint text-dependent speaker verification." In Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, pp. 4052-4056. IEEE, 2014. paper

Reference for CNN: Chen, Y. H., Lopez-Moreno, I., Sainath, T. N., Visontai, M., Alvarez, R., & Parada, C. (2015). Locally-connected and convolutional neural networks for small footprint speaker recognition. In Sixteenth Annual Conference of the International Speech Communication Association. paper

data: WSJ and LibriSpeech Corpus
features: 32 dimensional log filterbank generated using HTK Toolkit
labels: labels are force aligned using ASR Model built using Kaldi's WSJ recipe.

Work was done at Learning and Extraction of Acoustic Pattern Lab, IISc under the guidance of Prof. Sriram Ganapathy

About

Implementation of state of the art d-vector approach for speaker verification

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%