Jan Černocký


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Legal and Ethical Challenges in Recording Air Traffic Control Speech
Mickaël Rigault | Claudia Cevenini | Khalid Choukri | Martin Kocour | Karel Veselý | Igor Szoke | Petr Motlicek | Juan Pablo Zuluaga-Gomez | Alexander Blatt | Dietrich Klakow | Allan Tart | Pavel Kolčárek | Jan Černocký
Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference


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hari Krishna Vydana | Martin Karafiat | Lukas Burget | Jan Černocký
Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)

The paper describes BUT’s English to German offline speech translation (ST) systems developed for IWSLT2021. They are based on jointly trained Automatic Speech Recognition-Machine Translation models. Their performances is evaluated on MustC-Common test set. In this work, we study their efficiency from the perspective of having a large amount of separate ASR training data and MT training data, and a smaller amount of speech-translation training data. Large amounts of ASR and MT training data are utilized for pre-training the ASR and MT models. Speech-translation data is used to jointly optimize ASR-MT models by defining an end-to-end differentiable path from speech to translations. For this purpose, we use the internal continuous representations from the ASR-decoder as the input to MT module. We show that speech translation can be further improved by training the ASR-decoder jointly with the MT-module using large amount of text-only MT training data. We also show significant improvements by training an ASR module capable of generating punctuated text, rather than leaving the punctuation task to the MT module.


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Orthographic and Phonetic Annotation of Very Large Czech Corpora with Quality Assessment
Petr Pollák | Jan Černocký
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)