This paper presents CoDipA UNSC 1.0, a Corpus of Diplomatic Attitudes of the United Nations Security Council annotated with the attitude-part of the Appraisal theory. The speeches were manually selected according to topic-related and temporal criteria. The texts were then annotated according to the predefined annotation scenario. The distinguishing features of the diplomatic texts require a modified approach to attitude evaluation, which was implemented and presented in the current work. The corpus analysis has proven diplomatic speeches to be consistently evaluative, offered an overview of the most prominent means of expressing subjectivity in the corpus, and provided the results of the inter-annotator agreement evaluation.

We present Charles Translator, a machine translation system between Ukrainian and Czech, developed as part of a society-wide effort to mitigate the impact of the Russian-Ukrainian war on individuals and society. The system was developed in the spring of 2022 with the help of many language data providers in order to quickly meet the demand for such a service, which was not available at the time in the required quality. The translator was later implemented as an online web interface and as an Android app with speech input, both featuring Cyrillic-Latin script transliteration. The system translates directly, in comparison to other available systems that use English as a pivot, and thus makes advantage of the typological similarity of the two languages. It uses the block back-translation method which allows for efficient use of monolingual training data. The paper describes the development process including data collection and implementation, evaluation, mentions several use cases and outlines possibilities for further development of the system for educational purposes.