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Found 17 papers, 4 papers with code
Latvian National Corpora Collection – Korpuss.lv
LNCC is a diverse collection of Latvian language corpora representing both written and spoken language and is useful for both linguistic research and language modelling.
Cultural Vocal Bursts Intensity Prediction
Language Modelling
RIGA at SemEval-2022 Task 1: Scaling Recurrent Neural Networks for CODWOE Dictionary Modeling
Described are our two entries “emukans” and “guntis” for the definition modeling track of CODWOE SemEval-2022 Task 1.
Discrete Denoising Diffusion Approach to Integer Factorization
Integer factorization is a famous computational problem unknown whether being solvable in the polynomial time.
Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe
It has long been speculated that deep neural networks function by discovering a hierarchical set of domain-specific core concepts or patterns, which are further combined to recognize even more elaborate concepts for the classification or other machine learning tasks.
Multilingual Clustering of Streaming News
Clustering news across languages enables efficient media monitoring by aggregating articles from multilingual sources into coherent stories.
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.
The SUMMA Platform Prototype
We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
The Role of CNL and AMR in Scalable Abstractive Summarization for Multilingual Media Monitoring
In the era of Big Data and Deep Learning, there is a common view that machine learning approaches are the only way to cope with the robust and scalable information extraction and summarization.
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
Polysemy in Controlled Natural Language Texts
We show that micro-ontologies and multi-word units allow integration of the rich and polysemous multi-domain background knowledge into CNL thus providing interpretation for the content words.
FrameNet Resource Grammar Library for GF
In this paper we are focusing on verbs, investigating the possibility of creating a multilingual FrameNet-based GF library.
FrameNet CNL: a Knowledge Representation and Information Extraction Language
The paper presents a FrameNet-based information extraction and knowledge representation framework, called FrameNet-CNL.
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.
