Meet us at
Events Attended
Publications
- “Comparative Study on Sentence Boundary Prediction for German and English Broadcast News”, Yang Wang, Alexandre Nanchen, Alexandros Lazaridis, David Imseng, and Philip N. Garner, In Interspeech 2017 (submitted)
- “The SUMMA Platform Prototype”, Ulrich Germann, Renars Liepins, et al. In 2017 EACL Demo Track
Prototypes and technologies
The SUMMA Platform is a tool for aggregating and analysing various news items (text, audio, video). The Platform consists of multiple NLP (natural language processing) modules, including Automatic Speech Recognition (ASR), Machine Translation (MT), Named Entity Linking (NEL), Knowledge Data Base (KDB) , event clustering, topic detection, sentiment detection and story-line summarisation. Each module is developed independently by a team that is focused on that module. The goal of the Baseline Architecture is to provide a maximum independence so that each team is free to choose whatever technologies are most appropriate, on the condition that each module honours the API contract.