Publication Details
Analysis of Multilingual BLSTM Acoustic Model on Lowand High Resource Languages
KARAFIÁT Martin, BASKAR Murali K., VESELÝ Karel, GRÉZL František, BURGET Lukáš and ČERNOCKÝ Jan. Analysis of Multilingual BLSTM Acoustic Model on Lowand High Resource Languages. In: Proceedings of ICASSP 2018. Calgary: IEEE Signal Processing Society, 2018, pp. 5789-5793. ISBN 978-1-5386-4658-8.
Czech title
Analyýza mlutilingválního akustického modelu založeného na BLSTM pro jazyky s omezenými a bohatými zdroji
Type
conference paper
Language
english
Authors
Karafiát Martin, Ing., Ph.D. (DCGM FIT BUT)
Baskar Murali K. (DCGM FIT BUT)
Veselý Karel, Ing., Ph.D. (DCGM FIT BUT)
Grézl František, Ing., Ph.D. (DCGM FIT BUT)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Černocký Jan, doc. Dr. Ing. (DCGM FIT BUT)
Baskar Murali K. (DCGM FIT BUT)
Veselý Karel, Ing., Ph.D. (DCGM FIT BUT)
Grézl František, Ing., Ph.D. (DCGM FIT BUT)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Černocký Jan, doc. Dr. Ing. (DCGM FIT BUT)
URL
Keywords
Automatic speech recognition, Multilingual
neural networks, Bidirectional Long Short Term Memory
Abstract
The paper provides an analysis of automatic speech recognition
systems (ASR) based on multilingual BLSTM, where we
used multi-task training with separate classification layer for
each language. The focus is on low resource languages, where
only a limited amount of transcribed speech is available. In
such scenario, we found it essential to train the ASR systems
in a multilingual fashion and we report superior results
obtained with pre-trained multilingual BLSTM on this task.
The high resource languages are also taken into account and
we show the importance of language richness for multilingual
training. Next, we present the performance of this technique
as a function of amount of target language data. The importance
of including context information into BLSTM multilingual
systems is also stressed, and we report increased resilience
of large NNs to overtraining in case of multi-task
training.
Published
2018
Pages
5789-5793
Proceedings
Proceedings of ICASSP 2018
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, CA
ISBN
978-1-5386-4658-8
Publisher
IEEE Signal Processing Society
Place
Calgary, CA
DOI
BibTeX
@INPROCEEDINGS{FITPUB11720, author = "Martin Karafi\'{a}t and K. Murali Baskar and Karel Vesel\'{y} and Franti\v{s}ek Gr\'{e}zl and Luk\'{a}\v{s} Burget and Jan \v{C}ernock\'{y}", title = "Analysis of Multilingual BLSTM Acoustic Model on Lowand High Resource Languages", pages = "5789--5793", booktitle = "Proceedings of ICASSP 2018", year = 2018, location = "Calgary, CA", publisher = "IEEE Signal Processing Society", ISBN = "978-1-5386-4658-8", doi = "10.1109/ICASSP.2018.8462083", language = "english", url = "https://www.fit.vut.cz/research/publication/11720" }