no code implementations • IWSLT (ACL) 2022 • Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, Marcely Zanon Boito, Ondřej Bojar, Roldano Cattoni, Anna Currey, Georgiana Dinu, Kevin Duh, Maha Elbayad, Clara Emmanuel, Yannick Estève, Marcello Federico, Christian Federmann, Souhir Gahbiche, Hongyu Gong, Roman Grundkiewicz, Barry Haddow, Benjamin Hsu, Dávid Javorský, Vĕra Kloudová, Surafel Lakew, Xutai Ma, Prashant Mathur, Paul McNamee, Kenton Murray, Maria Nǎdejde, Satoshi Nakamura, Matteo Negri, Jan Niehues, Xing Niu, John Ortega, Juan Pino, Elizabeth Salesky, Jiatong Shi, Matthias Sperber, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Yogesh Virkar, Alexander Waibel, Changhan Wang, Shinji Watanabe
The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.
no code implementations • 4 Aug 2023 • Yogesh Virkar, Brian Thompson, Rohit Paturi, Sundararajan Srinivasan, Marcello Federico
The media localization industry usually requires a verbatim script of the final film or TV production in order to create subtitles or dubbing scripts in a foreign language.
no code implementations • 22 May 2023 • Proyag Pal, Brian Thompson, Yogesh Virkar, Prashant Mathur, Alexandra Chronopoulou, Marcello Federico
To translate speech for automatic dubbing, machine translation needs to be isochronous, i. e. translated speech needs to be aligned with the source in terms of speech durations.
1 code implementation • 25 Feb 2023 • Alexandra Chronopoulou, Brian Thompson, Prashant Mathur, Yogesh Virkar, Surafel M. Lakew, Marcello Federico
Automatic dubbing (AD) is the task of translating the original speech in a video into target language speech.
1 code implementation • 23 Dec 2022 • William Brannon, Yogesh Virkar, Brian Thompson
We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319. 57 hours of video from 54 professionally produced titles.
no code implementations • 6 Apr 2022 • Yogesh Virkar, Marcello Federico, Robert Enyedi, Roberto Barra-Chicote
The goal of automatic dubbing is to perform speech-to-speech translation while achieving audiovisual coherence.
no code implementations • 16 Dec 2021 • Derek Tam, Surafel M. Lakew, Yogesh Virkar, Prashant Mathur, Marcello Federico
We introduce the task of isochrony-aware machine translation which aims at generating translations suitable for dubbing.
no code implementations • 16 Dec 2021 • Surafel M. Lakew, Yogesh Virkar, Prashant Mathur, Marcello Federico
Automatic dubbing (AD) is among the machine translation (MT) use cases where translations should match a given length to allow for synchronicity between source and target speech.
no code implementations • 8 Oct 2021 • Surafel M. Lakew, Marcello Federico, Yue Wang, Cuong Hoang, Yogesh Virkar, Roberto Barra-Chicote, Robert Enyedi
Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language.