DocumentCode
3020282
Title
Survey of Automated Speaker Identification Methods
Author
Sidorov, Maxim ; Schmitt, Andreas ; Zablotskiy, Sergey ; Minker, Wolfgang
Author_Institution
Inst. of Commun. Eng., Univ. of Ulm, Ulm, Germany
fYear
2013
fDate
16-17 July 2013
Firstpage
236
Lastpage
239
Abstract
In this paper we present an overview of state-of-the-art approaches for speaker identification. Due to the increased number of dialogue system applications the interest in that field has grown significantly in recent years. Nevertheless, there are many open issues in the field of automatic speaker identification. Among them the choice of the appropriate speech signal features and machine learning algorithms could be mentioned. We make here an overview of modern methods designed for the problem of speaker identification. We also describe here our direction for possible improvements to the automated speaker identification.
Keywords
learning (artificial intelligence); speaker recognition; automated speaker identification; dialogue system application; machine learning algorithm; speech signal features; Accuracy; Databases; Mel frequency cepstral coefficient; Speech; Support vector machines; Testing; Training; Gaussian mixture models; machine learning algorithms; speaker identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Environments (IE), 2013 9th International Conference on
Conference_Location
Athens
Type
conf
DOI
10.1109/IE.2013.31
Filename
6597817
Link To Document