Intra-cluster training strategy for deep learning with applications to language identification

Alan Joseph Bekker; Irit Opher; Itsik Lapidot; Jacob Goldberger

doi:10.1109/mlsp.2016.7738896

Intra-cluster training strategy for deep learning with applications to language identification

Alan Joseph Bekker, Irit Opher, Itsik Lapidot, Jacob Goldberger

Bar-Ilan University - The Alexander Kofkin Faculty of Engineering

Afeka Acad. Coll. of Eng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

In this study we address the problem of training a neural network for language identification using speech samples in the form of i-vectors. Our approach involves training a classifier and analyzing the obtained confusion matrix. We cluster the languages by simultaneously clustering the columns and the rows of the confusion matrix. The language clusters are then used to define a modified cost function for training a neural-network that focuses on distinguishing between the true language and languages within the same cluster. The results show enhanced language identification on the NIST 2015 language identification dataset.

Original language	English
Title of host publication	2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings
Editors	Kostas Diamantaras, Aurelio Uncini, Francesco A. N. Palmieri, Jan Larsen
Publisher	IEEE Computer Society
ISBN (Electronic)	9781509007462
DOIs	https://doi.org/10.1109/mlsp.2016.7738896
State	Published - 8 Nov 2016
Event	26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings - Vietri sul Mare, Salerno, Italy Duration: 13 Sep 2016 → 16 Sep 2016

Publication series

Name	IEEE International Workshop on Machine Learning for Signal Processing, MLSP
Volume	2016-November
ISSN (Print)	2161-0363
ISSN (Electronic)	2161-0371

Conference

Conference	26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings
Country/Territory	Italy
City	Vietri sul Mare, Salerno
Period	13/09/16 → 16/09/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Confusion matrix
clustering
language identification

Access to Document

10.1109/mlsp.2016.7738896

Cite this

Bekker, A. J., Opher, I., Lapidot, I., & Goldberger, J. (2016). Intra-cluster training strategy for deep learning with applications to language identification. In K. Diamantaras, A. Uncini, F. A. N. Palmieri, & J. Larsen (Eds.), 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings Article 7738896 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/mlsp.2016.7738896

Bekker, Alan Joseph ; Opher, Irit ; Lapidot, Itsik et al. / Intra-cluster training strategy for deep learning with applications to language identification. 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. editor / Kostas Diamantaras ; Aurelio Uncini ; Francesco A. N. Palmieri ; Jan Larsen. IEEE Computer Society, 2016. (IEEE International Workshop on Machine Learning for Signal Processing, MLSP).

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abstract = "In this study we address the problem of training a neural network for language identification using speech samples in the form of i-vectors. Our approach involves training a classifier and analyzing the obtained confusion matrix. We cluster the languages by simultaneously clustering the columns and the rows of the confusion matrix. The language clusters are then used to define a modified cost function for training a neural-network that focuses on distinguishing between the true language and languages within the same cluster. The results show enhanced language identification on the NIST 2015 language identification dataset.",

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doi = "10.1109/mlsp.2016.7738896",

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Bekker, AJ, Opher, I, Lapidot, I & Goldberger, J 2016, Intra-cluster training strategy for deep learning with applications to language identification. in K Diamantaras, A Uncini, FAN Palmieri & J Larsen (eds), 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings., 7738896, IEEE International Workshop on Machine Learning for Signal Processing, MLSP, vol. 2016-November, IEEE Computer Society, 26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings, Vietri sul Mare, Salerno, Italy, 13/09/16. https://doi.org/10.1109/mlsp.2016.7738896

Intra-cluster training strategy for deep learning with applications to language identification. / Bekker, Alan Joseph; Opher, Irit; Lapidot, Itsik et al.
2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. ed. / Kostas Diamantaras; Aurelio Uncini; Francesco A. N. Palmieri; Jan Larsen. IEEE Computer Society, 2016. 7738896 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; Vol. 2016-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Bekker AJ, Opher I, Lapidot I, Goldberger J. Intra-cluster training strategy for deep learning with applications to language identification. In Diamantaras K, Uncini A, Palmieri FAN, Larsen J, editors, 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. IEEE Computer Society. 2016. 7738896. (IEEE International Workshop on Machine Learning for Signal Processing, MLSP). doi: 10.1109/mlsp.2016.7738896

Intra-cluster training strategy for deep learning with applications to language identification

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