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Detail publikačního výsledku
VESELÝ, K.; BASKAR, M.; DIEZ SÁNCHEZ, M.; BENEŠ, K.
Originální název
MGB-3 but system: Low-resource ASR on Egyptian YouTube data
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
This paper presents a series of experiments we performed duringour work on the MGB-3 evaluations. We both describethe submitted system, as well as the post-evaluation analysis.Our initial BLSTM-HMM system was trained on 250 hoursof MGB-2 data (Al-Jazeera), it was adapted with 5 hours ofEgyptian data (YouTube). We included such techniques asdiarization, n-gram language model adaptation, speed perturbationof the adaptation data, and the use of all 4 correctreferences. The 4 references were either used for supervisionwith a confusion network, or we included each sentence 4xwith the transcripts from all the annotators. Then, it was alsohelpful to blend the augmented MGB-3 adaptation data with15 hours of MGB-2 data. Although we did not rank with oursingle system among the best teams in the evaluations, we believethat our analysis will be highly interesting not only forthe other MGB-3 challenge participants.
Anglický abstrakt
Klíčová slova
MGB-3, ASR adaptation, low-resource ASR, Egyptian Arabic, diarization
Klíčová slova v angličtině
Autoři
Rok RIV
2018
Vydáno
16.12.2017
Nakladatel
IEEE Signal Processing Society
Místo
Okinawa
ISBN
978-1-5090-4788-8
Kniha
Proceedings of ASRU 2017
Strany od
368
Strany do
373
Strany počet
6
URL
https://www.fit.vut.cz/research/publication/11595/
BibTex
@inproceedings{BUT144502, author="Karel {Veselý} and Murali Karthick {Baskar} and Mireia {Diez Sánchez} and Karel {Beneš}", title="MGB-3 but system: Low-resource ASR on Egyptian YouTube data", booktitle="Proceedings of ASRU 2017", year="2017", pages="368--373", publisher="IEEE Signal Processing Society", address="Okinawa", doi="10.1109/ASRU.2017.8268959", isbn="978-1-5090-4788-8", url="https://www.fit.vut.cz/research/publication/11595/" }
Dokumenty
vesely_asru2017_mgb3-paper