Detail publikace
Lightly supervised vs. semi-supervised training of acoustic model on Luxembourgish for low-resource automatic speech recognition
VESELÝ, K. PERALES, C. SZŐKE, I. LUQUE, J. ČERNOCKÝ, J.
Originální název
Lightly supervised vs. semi-supervised training of acoustic model on Luxembourgish for low-resource automatic speech recognition
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
In this work, we focus on exploiting inexpensive data in orderto to improve the DNN acoustic model for ASR. We exploretwo strategies: The first one uses untranscribed data fromthe target domain. The second one is related to the proper selectionof excerpts from imperfectly transcribed out-of-domainpublic data, as parliamentary speeches. We found out that bothapproaches lead to similar results, making them equally beneficialfor practical use. The Luxembourgish ASR seed systemhad a 38.8% WER and it improved by roughly 4% absolute,leading to 34.6% for untranscribed and 34.9% for lightlysuperviseddata. Adding both databases simultaneously ledto 34.4% WER, which is only a small improvement. As asecondary research topic, we experiment with semi-supervisedstate-level minimum Bayes risk (sMBR) training. Nonetheless,for sMBR we saw no improvement from adding the automaticallytranscribed target data, despite that similar techniquesyield good results in the case of cross-entropy (CE) training.
Klíčová slova
Luxembourgish, call centers, speech recognition,low-resourced ASR, unsupervised training
Autoři
VESELÝ, K.; PERALES, C.; SZŐKE, I.; LUQUE, J.; ČERNOCKÝ, J.
Vydáno
2. 9. 2018
Nakladatel
International Speech Communication Association
Místo
Hyderabad
ISSN
1990-9772
Periodikum
Proceedings of Interspeech
Ročník
2018
Číslo
9
Stát
Francouzská republika
Strany od
2883
Strany do
2887
Strany počet
5
URL
BibTex
@inproceedings{BUT155104,
author="VESELÝ, K. and PERALES, C. and SZŐKE, I. and LUQUE, J. and ČERNOCKÝ, J.",
title="Lightly supervised vs. semi-supervised training of acoustic model on Luxembourgish for low-resource automatic speech recognition",
booktitle="Proceedings of Interspeech 2018",
year="2018",
journal="Proceedings of Interspeech",
volume="2018",
number="9",
pages="2883--2887",
publisher="International Speech Communication Association",
address="Hyderabad",
doi="10.21437/Interspeech.2018-2361",
issn="1990-9772",
url="https://www.isca-speech.org/archive/Interspeech_2018/abstracts/2361.html"
}
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