Project Details
IARPA Machine Translation for English Retrieval of Information in Any Language (MATERIAL) - Foreign Language Automated Information Retrieval (FLAIR)
Project Period: 21. 9. 2017 – 22. 10. 2021
Project Type: contract
Partner: Intelligence Advanced Research Projects Activity
machine translation, automatic speech regcognition, language identification,
summarization
MATERIAL aims at developing an "English-in, English-out" information retrieval
system that, given a domain-sensitive English query, will retrieve relevant data
from a large multilingual repository and display the retrieved information in
English as query-biased summaries.
Baskar Murali Karthick, Ing., Ph.D.
Beneš Karel, Ing. (DCGM)
Burget Lukáš, doc. Ing., Ph.D. (DCGM)
Diez Sánchez Mireia, M.Sc., Ph.D. (DCGM)
Egorova Ekaterina, Ing., Ph.D.
Filip David, Mgr. et Mgr., Ph.D.
Glembek Ondřej, Ing., Ph.D.
Grézl František, Ing., Ph.D. (DCGM)
Kesiraju Santosh, Ph.D. (DCGM)
Landini Federico Nicolás, Ph.D. (RG SPEECH)
Matějka Pavel, Ing., Ph.D.
Mošner Ladislav, Ing. (DCGM)
Novotný Ondřej, Ing., Ph.D.
Ondel Lucas Antoine Francois, Mgr., Ph.D. (SSDIT)
Plchot Oldřich, Ing., Ph.D. (DCGM)
Pulugundla Bhargav, M.Sc.
Rohdin Johan Andréas, M.Sc., Ph.D. (DCGM)
Sagar Sangeet
Skácel Miroslav, Ing.
Szőke Igor, Ing., Ph.D. (DCGM)
Veselý Karel, Ing., Ph.D. (DCGM)
Vydana Hari Krishna
2021
- KARAFIÁT, M.; VESELÝ, K.; ČERNOCKÝ, J.; PROFANT, J.; NYTRA, J.; HLAVÁČEK, M.; PAVLÍČEK, T. Analysis of X-Vectors for Low-Resource Speech Recognition. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Toronto, Ontario: IEEE Signal Processing Society, 2021.
p. 6998-7002. ISBN: 978-1-7281-7605-5. Detail - VYDANA, H.; KARAFIÁT, M.; ŽMOLÍKOVÁ, K.; BURGET, L.; ČERNOCKÝ, J. Jointly Trained Transformers Models for Spoken Language Translation. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Toronto, Ontario: IEEE Signal Processing Society, 2021.
p. 7513-7517. ISBN: 978-1-7281-7605-5. Detail
2019
- BASKAR, M.; BURGET, L.; WATANABE, S.; KARAFIÁT, M.; HORI, T.; ČERNOCKÝ, J. Promising Accurate Prefix Boosting For Sequence-to-sequence ASR. In Proceedings of ICASSP. Brighton: IEEE Signal Processing Society, 2019.
p. 5646-5650. ISBN: 978-1-5386-4658-8. Detail - BASKAR, M.; WATANABE, S.; ASTUDILLO, R.; HORI, T.; BURGET, L.; ČERNOCKÝ, J. Semi-supervised Sequence-to-sequence ASR using Unpaired Speech and Text. In Proceedings of Interspeech. Proceedings of Interspeech. Graz: International Speech Communication Association, 2019.
p. 3790-3794. ISSN: 1990-9772. Detail - KARAFIÁT, M.; BASKAR, M.; WATANABE, S.; HORI, T.; WIESNER, M.; ČERNOCKÝ, J. Analysis of Multilingual Sequence-to-Sequence Speech Recognition Systems. In Proceedings of Interspeech. Proceedings of Interspeech. Graz: International Speech Communication Association, 2019.
p. 2220-2224. ISSN: 1990-9772. Detail - ONDEL YANG, L.; VYDANA, H.; BURGET, L.; ČERNOCKÝ, J. Bayesian Subspace Hidden Markov Model for Acoustic Unit Discovery. In Proceedings of Interspeech 2019. Proceedings of Interspeech. Graz: International Speech Communication Association, 2019.
p. 261-265. ISSN: 1990-9772. Detail
2017
- KARAFIÁT, M. Summary report for project Machine Translation for English Retrieval of Information in Any Language (MATERIAL) For year 2017. Brno: Raytheon BBN Technologies, 2017.
p. 1-2. Detail