Actress Mary Jansová with her colleagues Josef Rovenský and Luigi Hofman in Pohorská vesnice (Mountain Village, dir. Miroslav Josef Krňanský, 1928). Jansová in Karel Havlíček Borovský, a film now considered lost (dir. Karel Lamač, Theodor Pištěk, 1925).
Painter Maryna Alšová and her husband Emanuel Svoboda in their flat. Alšová and Emanuel Svoboda, a biographer of Mikoláš Aleš, with painter Jaroslav Háša on a park bench.
Painter Max Švabinský speaking at the opening of his exhibition at the Mánes Exhibition Hall in Prague in a segment from Československý filmový týdeník (Czechoslovak Film Weekly Newsreel) 1933, issue no. 39. Švabinský with Taťjana Nilovna Jablonská in a segment from Československé filmové noviny (Czechoslovak Film News) 1951, issue no. 47. Švabinský at the exhibition held to mark his 80th birthday in a fragmented segment from Československý filmový týdeník (Czechoslovak Film Weekly Newsreel) 1953, issue no. 42.
En-De translation models, exported via TensorFlow Serving, available in the Lindat translation service (https://lindat.mff.cuni.cz/services/translation/).
The models were trained using the MCSQ social surveys dataset (available at https://repo.clarino.uib.no/xmlui/bitstream/handle/11509/142/mcsq_v3.zip).
Their main use should be in-domain translation of social surveys.
Models are compatible with Tensor2tensor version 1.6.6.
For details about the model training (data, model hyper-parameters), please contact the archive maintainer.
Evaluation on MCSQ test set (BLEU):
en->de: 67.5 (train: genuine in-domain MCSQ data only)
de->en: 75.0 (train: additional in-domain backtranslated MCSQ data)
(Evaluated using multeval: https://github.com/jhclark/multeval)
En-Ru translation models, exported via TensorFlow Serving, available in the Lindat translation service (https://lindat.mff.cuni.cz/services/translation/).
The models were trained using the MCSQ social surveys dataset (available at https://repo.clarino.uib.no/xmlui/bitstream/handle/11509/142/mcsq_v3.zip).
Their main use should be in-domain translation of social surveys.
Models are compatible with Tensor2tensor version 1.6.6.
For details about the model training (data, model hyper-parameters), please contact the archive maintainer.
Evaluation on MCSQ test set (BLEU):
en->ru: 64.3 (train: genuine in-domain MCSQ data)
ru->en: 74.7 (train: additional backtranslated in-domain MCSQ data)
(Evaluated using multeval: https://github.com/jhclark/multeval)
MEd is an annotation tool in which linearly-structured annotations of text or audio data can be created and edited. The tool supports multiple stacked layers of annotations that can be interconnected by links. MEd can also be used for other purposes, such as word-to-word alignment of parallel corpora.