Search Results for author:
Found 7 papers, 2 papers with code
The SUMMA Platform: A Scalable Infrastructure for Multi-lingual Multi-media Monitoring
The open-source SUMMA Platform is a highly scalable distributed architecture for monitoring a large number of media broadcasts in parallel, with a lag behind actual broadcast time of at most a few minutes.
Integrating Multiple NLP Technologies into an Open-source Platform for Multilingual Media Monitoring
The open-source SUMMA Platform is a highly scalable distributed architecture for monitoring a large number of media broadcasts in parallel, with a lag behind actual broadcast time of at most a few minutes.
RIGOTRIO at SemEval-2017 Task 9: Combining Machine Learning and Grammar Engineering for AMR Parsing and Generation
By addressing both text-to-AMR parsing and AMR-to-text generation, SemEval-2017 Task 9 established AMR as a powerful semantic interlingua.
RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracy
The first extension com-bines the smatch scoring script with the C6. 0 rule-based classifier to produce a human-readable report on the error patterns frequency observed in the scored AMR graphs.
Character-Level Neural Translation for Multilingual Media Monitoring in the SUMMA Project
The results of this paper describe a novel approach to the automatic story segmentation and storyline clustering problem.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
Using C5.0 and Exhaustive Search for Boosting Frame-Semantic Parsing Accuracy
Frame-semantic parsing is a kind of automatic semantic role labeling performed according to the FrameNet paradigm.
