Project Details

Rozpoznávání řeči pro jazyky s omezeným množstvím trénovacích zdrojů

Project Period: 1. 1. 2012 – 31. 12. 2014

Project Type: grant

Code: GPP202/12/P604

Agency: Czech Science Foundation

Program: Postdoktorandské granty

English title
Speech recognition for low-resource languages
Type
grant
Keywords

speech recognition, multilingual speech recognition, automatic dictionary
generation, SGMM

Abstract

The project aims at speech recognition in situations, where little training data
and limited or no knowledge of liguistic and phonetics of the target language are
available. In the domain of acoustic models, we will investigate modern
techniques of GMM/HMM parameter representations in sub-spaces. The project will
also focus on unsupervised creation of pronunciation dictionaries where sequences
of phonemes will be replaced by graphemes or clusters of acoustic unites trained
on data. Important parts of the project are tests on standard data and
participation in international evaluations.

Team members
Karafiát Martin, Ing., Ph.D. (DCGM) – research leader
Janda Miloš, Ing.
Publications

2014

  • GRÉZL, F.; EGOROVA, E.; KARAFIÁT, M. Further Investigation into Multilingual Training and Adaptation of Stacked Bottle-neck Neural Network Structure. In Proceedings of 2014 Spoken Language Technology Workshop. South Lake Tahoe, Nevada: IEEE Signal Processing Society, 2014. p. 48-53. ISBN: 978-1-4799-7129-9. Detail
  • GRÉZL, F.; KARAFIÁT, M. Adapting Multilingual Neural Network Hierarchy to a New Language. Proceedings of the 4th International Workshop on Spoken Language Technologies for Under- resourced Languages SLTU-2014. St. Petersburg, Russia, 2014. St. Petersburg: International Speech Communication Association, 2014. p. 39-45. ISBN: 978-5-8088-0908-6. Detail
  • GRÉZL, F.; KARAFIÁT, M. Combination of Multilingual and Semi-Supervised Training for Under-Resourced Languages. In Proceedings of Interspeech 2014. Singapore: International Speech Communication Association, 2014. p. 820-824. ISBN: 978-1-63439-435-2. Detail
  • GRÉZL, F.; KARAFIÁT, M.; VESELÝ, K. Adaptation of Multilingual Stacked Bottle-neck Neural Network Structure for New Language. In Proceedings of ICASSP 2014. Florencie: IEEE Signal Processing Society, 2014. p. 7704-7708. ISBN: 978-1-4799-2892-7. Detail
  • KARAFIÁT, M.; GRÉZL, F.; HANNEMANN, M.; ČERNOCKÝ, J. BUT Neural Network Features for Spontaneous Vietnamese in BABEL. In Proceedings of ICASSP 2014. Florencie: IEEE Signal Processing Society, 2014. p. 5659-5663. ISBN: 978-1-4799-2892-7. Detail
  • KARAFIÁT, M.; GRÉZL, F.; VESELÝ, K.; HANNEMANN, M.; SZŐKE, I.; ČERNOCKÝ, J. BUT 2014 Babel System: Analysis of adaptation in NN based systems. In Proceedings of Interspeech 2014. Singapore: International Speech Communication Association, 2014. p. 3002-3006. ISBN: 978-1-63439-435-2. Detail
  • KARAFIÁT, M.; VESELÝ, K.; SZŐKE, I.; BURGET, L.; GRÉZL, F.; HANNEMANN, M.; ČERNOCKÝ, J. BUT ASR System for BABEL Surprise Evaluation 2014. In Proceedings of 2014 Spoken Language Technology Workshop. South Lake Tahoe, Nevada: IEEE Signal Processing Society, 2014. p. 501-506. ISBN: 978-1-4799-7129-9. Detail
  • NG, T.; HSIAO, R.; ZHANG, L.; KARAKOS, D.; MALLIDI, S.; KARAFIÁT, M.; VESELÝ, K.; SZŐKE, I.; ZHANG, B.; NGUYEN, L.; SCHWARTZ, R. Progress in the BBN Keyword Search System for the DARPA RATS Program. In Proceedings of Interspeech 2014. Singapore: International Speech Communication Association, 2014. p. 959-963. ISBN: 978-1-63439-435-2. Detail

2013

  • EGOROVA, E.; VESELÝ, K.; KARAFIÁT, M.; JANDA, M.; ČERNOCKÝ, J. Manual and Semi-Automatic Approaches to Building a Multilingual Phoneme Set. In Proceedings of ICASSP 2013. Vancouver: IEEE Signal Processing Society, 2013. p. 7324-7328. ISBN: 978-1-4799-0355-9. Detail
  • GRÉZL, F.; KARAFIÁT, M. Semi-Supervised Bootstrapping Approach For Neural Network Feature Extractor Training. Proceedings of ASRU 2013. Olomouc: IEEE Signal Processing Society, 2013. p. 470-475. ISBN: 978-1-4799-2755-5. Detail
  • KARAFIÁT, M.; GRÉZL, F.; HANNEMANN, M.; VESELÝ, K.; ČERNOCKÝ, J. BUT BABEL System for Spontaneous Cantonese. Proceedings of Interspeech 2013. Proceedings of the 14th Annual Conference of the International Speech Communication Association (Interspeech 2013). Lyon: International Speech Communication Association, 2013. p. 2589-2593. ISBN: 978-1-62993-443-3. ISSN: 2308-457X. Detail
  • MOTLÍČEK, P.; POVEY, D.; KARAFIÁT, M. Feature And Score Level Combination Of Subspace Gaussians In LVCSR Task. Proceedings of ICASSP 2013. Vancouver: IEEE Signal Processing Society, 2013. p. 7604-7608. ISBN: 978-1-4799-0355-9. Detail

2012

  • KARAFIÁT, M.; JANDA, M.; ČERNOCKÝ, J.; BURGET, L. Region Dependent Linear Transforms in Multilingual Speech Recognition. In Proc. International Conference on Acoustics, Speech, and Signal Processing 2012. Kyoto: IEEE Signal Processing Society, 2012. p. 4885-4888. ISBN: 978-1-4673-0044-5. Detail
  • KOMBRINK, S.; MIKOLOV, T.; KARAFIÁT, M.; BURGET, L. Improving Language Models for ASR Using Translated In-domain Data. Proceedings of 2012 IEEE International Conference on Acoustics, Speech and Signal Processing. Kyoto: IEEE Signal Processing Society, 2012. p. 4405-4408. ISBN: 978-1-4673-0044-5. Detail
  • VESELÝ, K.; KARAFIÁT, M.; GRÉZL, F.; JANDA, M.; EGOROVA, E. The Language-Independent Bottleneck Features. Proceedings of IEEE 2012 Workshop on Spoken Language Technology. Miami: IEEE Signal Processing Society, 2012. p. 336-341. ISBN: 978-1-4673-5124-9. Detail
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