Detail výsledku
Bayesian phonotactic language model for Acoustic Unit Discovery
Burget Lukáš, doc. Ing., Ph.D., UPGM (FIT)
Černocký Jan, prof. Dr. Ing., UPGM (FIT)
Kesiraju Santosh, Ph.D., UPGM (FIT)
Recent work on Acoustic Unit Discovery (AUD) has led to the development of a non-parametric Bayesian phone-loop model where the prior over the probability of the phone-like units is assumed to be sampled from a Dirichlet Process (DP). In this work, we propose to improve this model by incorporating a Hierarchical Pitman-Yor based bigram Language Model on top of the units transitions. This new model makes use of the phonotactic context information but assumes a fixed number of units. To remedy this limitation we first train a DP phoneloop model to infer the number of units, then, the bigram phone-loop is initialized from the DP phone-loop and trained until convergence of its parameters. Results show an absolute improvement of 1-2%on the Normalized Mutual Information (NMI) metric. Furthermore, we show that, combined with Multilingual Bottleneck (MBN) features the model yields a same or higher NMI as an English phone recogniser trained on TIMIT.
Bayesian non-parametric, Variational Bayes, acoustic unit discovery
@inproceedings{BUT144452,
author="Lucas Antoine Francois {Ondel} and Lukáš {Burget} and Jan {Černocký} and Santosh {Kesiraju}",
title="Bayesian phonotactic language model for Acoustic Unit Discovery",
booktitle="Proceedings of ICASSP 2017",
year="2017",
pages="5750--5754",
publisher="IEEE Signal Processing Society",
address="New Orleans",
doi="10.1109/ICASSP.2017.7953258",
isbn="978-1-5090-4117-6",
url="https://www.fit.vut.cz/research/publication/11472/"
}
DARPA Jazyky s omezenými zdroji pro potenciální krizové situace (LORELEI) - Využití jazykové informace pro situační povědomí (ELISA, University of Southern California, zahájení: 2015-09-01, ukončení: 2020-03-31, ukončen
IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, zahájení: 2016-01-01, ukončení: 2020-12-31, ukončen