no code implementations • IWSLT 2016 • Ondřej Bojar, Ondřej Cífka, Jindřich Helcl, Tom Kocmi, Roman Sudarikov
We present our submissions to the IWSLT 2016 machine translation task, as our first attempt to translate subtitles and one of our early experiments with neural machine translation (NMT).
1 code implementation • 23 Nov 2023 • Ondřej Cífka, Constantinos Dimitriou, Cheng-i Wang, Hendrik Schreiber, Luke Miner, Fabian-Robert Stöter
Current automatic lyrics transcription (ALT) benchmarks focus exclusively on word content and ignore the finer nuances of written lyrics including formatting and punctuation, which leads to a potential misalignment with the creative products of musicians and songwriters as well as listeners' experiences.
Ranked #1 on Automatic Lyrics Transcription on Jam-ALT Spanish
1 code implementation • bioRxiv 2023 • Ondřej Cífka, Simon Chamaillé-Jammes, Antoine Liutkus
In this work, we propose MoveFormer, a new step-based model of movement capable of learning directly from full animal trajectories.
1 code implementation • 30 Dec 2022 • Ondřej Cífka, Antoine Liutkus
The increasingly widespread adoption of large language models has highlighted the need for improving their explainability.
1 code implementation • 18 May 2021 • Antoine Liutkus, Ondřej Cífka, Shih-Lun Wu, Umut Şimşekli, Yi-Hsuan Yang, Gaël Richard
Recent advances in Transformer models allow for unprecedented sequence lengths, due to linear space and time complexity.
1 code implementation • 10 Feb 2021 • Ondřej Cífka, Alexey Ozerov, Umut Şimşekli, Gaël Richard
While several style conversion methods tailored to musical signals have been proposed, most lack the 'one-shot' capability of classical image style transfer algorithms.
1 code implementation • IEEE/ACM Transactions on Audio, Speech, and Language Processing 2020 • Ondřej Cífka, Umut Şimşekli, Gaël Richard
Style transfer is the process of changing the style of an image, video, audio clip or musical piece so as to match the style of a given example.
1 code implementation • 4 Jul 2019 • Ondřej Cífka, Umut Şimşekli, Gaël Richard
Research on style transfer and domain translation has clearly demonstrated the ability of deep learning-based algorithms to manipulate images in terms of artistic style.
no code implementations • 16 May 2018 • Ondřej Cífka, Ondřej Bojar
One of possible ways of obtaining continuous-space sentence representations is by training neural machine translation (NMT) systems.
no code implementations • 21 Apr 2018 • Ondřej Cífka, Aliaksei Severyn, Enrique Alfonseca, Katja Filippova
In this paper, we study recent neural generative models for text generation related to variational autoencoders.