Detail publikace
A Hierarchical Subspace Model for Language-Attuned Acoustic Unit Discovery
YUSUF, B. ONDEL YANG, L. BURGET, L. ČERNOCKÝ, J. SARAÇLAR, M.
Originální název
A Hierarchical Subspace Model for Language-Attuned Acoustic Unit Discovery
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
In this work, we propose a hierarchical subspace model for acousticunit discovery. In this approach, we frame the task as one oflearning embeddings on a low-dimensional phonetic subspace, andsimultaneously specify the subspace itself as an embedding on a hyper-subspace. We train the hyper-subspace on a set of transcribedlanguages and transfer it to the target language. In the target language,we infer both the language and unit embeddings in an unsupervisedmanner, and in so doing, we simultaneously learn a subspaceof units specific to that language and the units that dwell on it.We conduct experiments on TIMIT and two low-resource languages:Mboshi and Yoruba. Results show that our model outperforms majoracoustic unit discovery techniques, both in terms of clusteringquality and segmentation accuracy.
Klíčová slova
acoustic unit discovery, hierarchical subspacemodel, unsupervised learning
Autoři
YUSUF, B.; ONDEL YANG, L.; BURGET, L.; ČERNOCKÝ, J.; SARAÇLAR, M.
Vydáno
6. 6. 2021
Nakladatel
IEEE Signal Processing Society
Místo
Toronto, Ontario
ISBN
978-1-7281-7605-5
Kniha
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Strany od
3710
Strany do
3714
Strany počet
5
URL
BibTex
@inproceedings{BUT175792,
author="YUSUF, B. and ONDEL YANG, L. and BURGET, L. and ČERNOCKÝ, J. and SARAÇLAR, M.",
title="A Hierarchical Subspace Model for Language-Attuned Acoustic Unit Discovery",
booktitle="ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
year="2021",
pages="3710--3714",
publisher="IEEE Signal Processing Society",
address="Toronto, Ontario",
doi="10.1109/ICASSP39728.2021.9414899",
isbn="978-1-7281-7605-5",
url="https://www.fit.vut.cz/research/publication/12523/"
}
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