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Citation

Marek Hrúz and Marie Kunešová : Convolutional Neural Network in the Task of Speaker Change Detection . Speech and Computer, 18th International Conference, SPECOM 2016, Lecture Notes in Computer Science, vol. 9811, p. 191-198, Springer, 2016.

Abstract

This paper presents an approach to detect speaker changes in telephone conversations. The speaker change problem is presented as a classification problem. We use a Convolutional Neural Network to analyze short audio segments. The Network plays a role of a regressor. It outputs higher values for segments that are more likely to contain a speaker change. Upon thresholding the regressed value the decision about the segment is made. The experiment shows that the Convolutional Neural Network outperforms a baseline system based on the Bayesian Information Criterion. It behaves very well on previously unseen data produced by previously unheard speakers.

Detail of publication

Title: Convolutional Neural Network in the Task of Speaker Change Detection
Author: Marek Hrúz ; Marie Kunešová
Language: English
Date of publication: 1 Aug 2016
Year: 2016
Type of publication: Papers in proceedings of reviewed conferences
Title of journal or book: Speech and Computer, 18th International Conference, SPECOM 2016
Series: Lecture Notes in Computer Science
Číslo vydání: 9811
Page: 191 - 198
DOI: 10.1007/978-3-319-43958-7_22
ISBN: 978-3-319-43957-0
Publisher: Springer
/ 2017-09-21 14:03:26 /

Keywords

Convolutional neural network, Speaker change detection, Spectrogram

BibTeX

@INPROCEEDINGS{MarekHruz_2016_ConvolutionalNeural,
 author = {Marek Hr\'{u}z and Marie Kune\v{s}ov\'{a}},
 title = {Convolutional Neural Network in the Task of Speaker Change Detection},
 year = {2016},
 publisher = {Springer},
 journal = {Speech and Computer, 18th International Conference, SPECOM 2016},
 volume = {9811},
 pages = {191-198},
 series = {Lecture Notes in Computer Science},
 ISBN = {978-3-319-43957-0},
 doi = {10.1007/978-3-319-43958-7_22},
 url = {http://www.kky.zcu.cz/en/publications/MarekHruz_2016_ConvolutionalNeural},
}