Blind Extraction of Moving Audio Source in a Challenging Environment Supported by Speaker Identification Via X-Vectors

Author(s):  
Jiri Malek ◽  
Jakub Jansky ◽  
Tomas Kounovsky ◽  
Zbynek Koldovsky ◽  
Jindrich Zdansky
2020 ◽  
pp. 65-72
Author(s):  
V. V. Savchenko ◽  
A. V. Savchenko

This paper is devoted to the presence of distortions in a speech signal transmitted over a communication channel to a biometric system during voice-based remote identification. We propose to preliminary correct the frequency spectrum of the received signal based on the pre-distortion principle. Taking into account a priori uncertainty, a new information indicator of speech signal distortions and a method for measuring it in conditions of small samples of observations are proposed. An example of fast practical implementation of the method based on a parametric spectral analysis algorithm is considered. Experimental results of our approach are provided for three different versions of communication channel. It is shown that the usage of the proposed method makes it possible to transform the initially distorted speech signal into compliance on the registered voice template by using acceptable information discrimination criterion. It is demonstrated that our approach may be used in existing biometric systems and technologies of speaker identification.


2015 ◽  
Vol 22 (1) ◽  
pp. 57-78 ◽  
Author(s):  
Peggy P.K. Mok ◽  
Robert Bo Xu ◽  
Donghui Zuo

2011 ◽  
Author(s):  
Chris Fill ◽  
Scot McKee

The once predictable world of business marketing is changing. It is now a complex and challenging environment populated by an increasing number of channels, fast developing technology, the expectation that everything and everyone is accountable, and characterised by changing buyer behaviours and an emphasis on conversations and connectedness. Despite these complexities and challenges, at the root of business marketing remains the need to find, develop and maintain relationships. Accordingly, this book is anchored to two main principles, namely, generating demand and building fruitful marketing-based relationships. To drive demand, establish relationships that are of mutual value, and to weave a route through the various complexities, it is important to understand the nature and changing perspectives of B2B buyers. From this knowledge, organisations are better placed to create more buyer-centric demand generation strategies. This book is underpinned and shaped by these ideas. Demand generation issues are recognised throughout the book and a chapter is dedicated to understanding relationship marketing principles.


Author(s):  
A. Nagesh

The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set of feature vectors using Gaussian Mixer model (GMM) for speaker identification. The MFCC are the default feature vectors for speaker recognition, but they are not very robust at the presence of additive noise. The GFCC features in recent studies have shown very good robustness against noise and acoustic change. The main idea is  GFCC features based on GMM feature extraction is to improve the overall speaker identification performance in low signal to noise ratio (SNR) conditions.


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