Segment from Československý zvukový týdeník Aktualita (Czechoslovak Aktualita Sound Newsreel) 1942, issue no. 28, depicts a public manifestation held on Wenceslas Square in Prague on 3 July 1942, which was to unequivocally condemn the assassination of Acting Reich Protector Reinhard Heydrich. The gathering was attended by 200,000 people. Wenceslas Square is decorated with Protectorate and Nazi flags. Footage of the crowded square and onlookers in the windows and on the roofs of surrounding houses. State President Emil Hácha, Prime Minister of the Protectorate Government Jaroslav Krejčí, Minister of the Interior Rudolf Bienert, and Minister of Education and People´s Enlightenment Emanuel Moravec stand on a grandstand. Krejčí and Moravec deliver speeches on cancelling the state of emergency and the need for active collaboration with the Reich. The manifestation concludes with the Czech anthem and people performing the Nazi salute, among them Minister of Finance Josef Kalfus, Minister of the Interior Rudolf Bienert, Prime Minister Jaroslav Krejčí, and Minister of Transport Jindřich Kamenický.
Footage from a manifestation in Uzhhorod in November 1919. Events following the General Statue that declared Subcarpathian Ruthenia as an autonomous part of the Czechoslovak Republic. Footage from a manifestation, from a ceremonial gathering on a square. Footage of soldiers and public speakers. A view of a bell covered with an American flag. Soldiers at the border. A military cemetery in winter. Ruthenians in fur coats and traditional clothes. People leaving a church. A group of people at a railway station.
Segment from Československý zvukový týdeník Aktualita (Czechoslovak Aktualita Sound Newsreel) 1942, issue no. 25, shows a meeting at the railway workshops in Pilsen held on 10 June 1942, at which the assassination of Acting Reich Protector Reinhard Heydrich was meant to be publicly and emphatically condemned. The meeting was attended by 12,000 people. Minister of Public Transport and Technology Jindřich Kamenický addresses employees in the public transport and technical services sector. Foreman Josef Fajfrlík expresses loyalty to the German Reich on behalf of railway and postal workers.
As a sub-section of MATEO, MARABU (Mannheimer Reihe Altes Buch) includes illustrated books, (manu)scripts and texts on the history of the Electoral Palatinate. Als Unterkategorie von MATEO beinhaltet MARABU (Mannheimer Reihe Altes Buch) illustrierte Bücher, Handschriften und Rarissima, Quellen zur Geschichte der Kurpfalz sowie Beiträge über Frauen des Humanismus.
The file represents a text corpus in the context of Arabic spell checking, where a group of persons edited different files, and all of the committed spelling errors by these persons have been recorded. A comprehensive representation these persons’ profile has been considered: male, female, old-aged, middle-aged, young-aged, high and low computer usage users, etc. Through this work, we aim to help researchers and those interested in Arabic NLP by providing them with an Arabic spell check corpus ready and open to exploitation and interpretation. This study also enabled the inventory of most spelling mistakes made by editors of Arabic texts. This file contains the following sections (tags): people – documents they printed – types of possible errors – errors they made. Each section (tag) contains some data that explains its details and its content, which helps researchers extracting research-oriented results. The people section contains basic information about each person and its relationship of using the computer, while the documents section clarifies all sentences in each document with the numbering of each sentence to be used in the errors section that was committed. We are also adding the “type of errors” section in which we list all the possible errors with their description in the Arabic language and give an illustrative example.
This data set contains four types of manual annotation of translation quality, focusing on the comparison of human and machine translation quality (aka human-parity). The machine translation system used is English-Czech CUNI Transformer (CUBBITT). The annotations distinguish adequacy, fluency and overall quality. One of the types is Translation Turing test - detecting whether the annotators can distinguish human from machine translation.
All the sentences are taken from the English-Czech test set newstest2018 (WMT2018 News translation shared task www.statmt.org/wmt18/translation-task.html), but only from the half with originally English sentences translated to Czech by a professional agency.
Manual classification of errors of Czech-Slovak translation according to the classification introduced by Vilar et al. [1]. First 50 sentences from WMT 2010 test set were translated by 5 MT systems (Česílko, Česílko2, Google Translate and two Moses setups) and MT errors were manually marked and classified. Classification was applied in MT systems comparison [3]. Reference translation is included.
References:
[1] David Vilar, Jia Xu, Luis Fernando D’Haro and Hermann Ney. Error Analysis of Machine Translation Output. In International Conference on Language Resources and Evaluation, pages 697-702. Genoa, Italy, May 2006.
[2] http://matrix.statmt.org/test_sets/list
[3] Ondřej Bojar, Petra Galuščáková, and Miroslav Týnovský. Evaluating Quality of Machine Translation from Czech to Slovak. In Markéta Lopatková, editor, Information Technologies - Applications and Theory, pages 3-9, September 2011 and This work has been supported by the grants Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and
7E09003 of the Czech Republic)
Manual classification of errors of English-Slovak translation according to the classification introduced by Vilar et al. [1]. 50 sentences randomly selected from WMT 2011 test set [2] were translated by 3 MT systems described in [3] and MT errors were manually marked and classified. Reference translation is included.
References:
[1] David Vilar, Jia Xu, Luis Fernando D’Haro and Hermann Ney. Error Analysis of Machine Translation Output. In International Conference on Language Resources and Evaluation, pages 697-702. Genoa, Italy, May 2006.
[2] http://www.statmt.org/wmt11/evaluation-task.html
[3] Petra Galuščáková and Ondřej Bojar. Improving SMT by Using Parallel Data of a Closely Related Language. In Human Language Technologies - The Baltic Perspective - Proceedings of the Fifth International Conference Baltic HLT 2012, volume 247 of Frontiers in AI and Applications, pages 58-65, Amsterdam, Netherlands, October 2012. IOS Press. and This work has been supported by the grant Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and
7E09003 of the Czech Republic)
Manually ranked outputs of Czech-Slovak translations. Three annotators manually ranked outputs of five MT systems (Česílko, Česílko2, Google Translate and two Moses setups) on three data sets (100 sentences randomly selected from books, 100 sentences randomly selected from Acquis corpus and 50 first sentences from WMT 2010 test set). Ranking was applied in MT systems comparison in [1].
References:
[1] Ondřej Bojar, Petra Galuščáková, and Miroslav Týnovský. Evaluating Quality of Machine Translation from Czech to Slovak. In Markéta Lopatková, editor, Information Technologies - Applications and Theory, pages 3-9, September 2011 and This work has been supported by the grant Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and
7E09003 of the Czech Republic)