An overview of speaker recognition
Article Sidebar
Main Article Content
Abstract
Speaker recognition has been studied for many years and has been a hot topic. This paper presents an overview of speaker recognition methods, which include the classical and the state-of-art methods. According to the modular components of speaker recognition system, we firstly introduced the fundamentals of speaker recognition, which are mainly divided into two parts: feature extraction and speaker modeling. The most commonly speech features used in speaker recognition were elaborated firstly. In particular, the recent progress of deep neural network proposes a new approach of feature extraction and has become the technology trend. Secondly, the classical approaches of speaker recognition model were introduced, and elaborated the recent progress of deep learning speaker recognition. This paper especially provides an in-depth analysis on end-to-end model which consists of a training component to extract features, an enrollment component to training the speaker model, and an evaluation component with appropriate loss function for optimization. The final part concludes the paper with discussion on future trends.
Downloads
Article Details
Copyright (c) 2019 Liu J, et al.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Licensing and protecting the author rights is the central aim and core of the publishing business. Peertechz dedicates itself in making it easier for people to share and build upon the work of others while maintaining consistency with the rules of copyright. Peertechz licensing terms are formulated to facilitate reuse of the manuscripts published in journals to take maximum advantage of Open Access publication and for the purpose of disseminating knowledge.
We support 'libre' open access, which defines Open Access in true terms as free of charge online access along with usage rights. The usage rights are granted through the use of specific Creative Commons license.
Peertechz accomplice with- [CC BY 4.0]
Explanation
'CC' stands for Creative Commons license. 'BY' symbolizes that users have provided attribution to the creator that the published manuscripts can be used or shared. This license allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to the author.
Please take in notification that Creative Commons user licenses are non-revocable. We recommend authors to check if their funding body requires a specific license.
With this license, the authors are allowed that after publishing with Peertechz, they can share their research by posting a free draft copy of their article to any repository or website.
'CC BY' license observance:
|
License Name |
Permission to read and download |
Permission to display in a repository |
Permission to translate |
Commercial uses of manuscript |
|
CC BY 4.0 |
Yes |
Yes |
Yes |
Yes |
The authors please note that Creative Commons license is focused on making creative works available for discovery and reuse. Creative Commons licenses provide an alternative to standard copyrights, allowing authors to specify ways that their works can be used without having to grant permission for each individual request. Others who want to reserve all of their rights under copyright law should not use CC licenses.