Cross-lingual document retrieval categorisation and navigation based on distributed services

The widespread use of the Internet across countries has increased the need for access to document collections that are often written in languages different from a user’s native language. In this paper we describe Clarity, a Cross Language Information Retrieval (CLIR) system for English, Finnish, Swedish, Latvian and Lithuanian. Clarity is a fully-fledged retrieval system that supports the user during the whole process of query formulation, text retrieval and document browsing. We address four of the major aspects of Clarity: (i) the user-driven methodology that formed the basis for the iterative design cycle and framework in the project, (ii) the system architecture that was developed to support the interaction and coordination of Clarity’s distributed services, (iii) the data resources and methods for query translation, and (iv) the support for Baltic languages. Clarity is an example of a distributed CLIR system built with minimal translation resources and, to our knowledge, the only such system that currently supports Baltic languages

Translation Quality and Productivity: A Study on Rich Morphology Languages.

This paper introduces a unique large-scale machine translation dataset with various levels of human annotation combined with automatically recorded productivity features such as time and keystroke logging and manual scoring during the annotation process. The data was collected as part of the EU-funded QT21 project and comprises 20,000–45,000 sentences of industry-generated content with translation into English and three morphologically rich languages: English–German/Latvian/Czech and German–English, in either the information technologyor life sciences domain. Altogether, the data consists of 176,476 tuples including a sourcesentence, the respective machine translation by a statistical system (additionally, by a neural system for two language pairs), a post-edited version of such translation by a native-speaking professional translator, an independently created reference translation, and information on post-editing: time, keystrokes, Likert scores, and annotator identifier. A subset of 2,000 sentences from this data per language pair and system type was also manually annotated with translation errors for deeper linguistic analysis. We describe the data collection process, provide a brief analysis of the resulting annotations and discuss the use of the data in quality estimation and automatic post-editing tasks

Media Suite: Unlocking Audiovisual Archives for Mixed Media Scholarly Research

This paper discusses the rationale behind and approach towards the development of a research environment –the Media Suite– in a sustainable, dynamic, multi-institutional infrastructure that supports mixed media scholarly research with large audiovisual data collections and available multimedia context collections, serving media scholars and digital humanists in general