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 :
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