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Found 12 papers, 0 papers with code
SpanAlign: Efficient Sequence Tagging Annotation Projection into Translated Data applied to Cross-Lingual Opinion Mining
Following the increasing performance of neural machine translation systems, the paradigm of using automatically translated data for cross-lingual adaptation is now studied in several applicative domains.
Analyse automatique en cadres s\'emantiques pour l'apprentissage de mod\`eles de compr\'ehension de texte (Semantic Frame Parsing for training Machine Reading Comprehension models)
Dans le cadre de la compr{\'e}hension automatique de documents, cet article propose une {\'e}valuation intrins{\`e}que et extrins{\`e}que d{'}un mod{\`e}le d{'}analyse automatique en cadres s{\'e}mantiques (Frames).
Analyse s\'emantique robuste par apprentissage antagoniste pour la g\'en\'eralisation de domaine (Robust Semantic Parsing with Adversarial Learning for Domain Generalization )
Nous pr{\'e}sentons des r{\'e}sum{\'e}s en fran{\c{c}}ais et en anglais de l{'}article (Marzinotto et al., 2019) pr{\'e}sent{\'e} {\`a} la conf{\'e}rence North American Chapter of the Association for Computational Linguistics : Human Language Technologies en 2019.
Cross-lingual and Cross-domain Evaluation of Machine Reading Comprehension with Squad and CALOR-Quest Corpora
Machine Reading received recently a lot of attention thanks to both the availability of very large corpora such as SQuAD or MS MARCO containing triplets (document, question, answer), and the introduction of Transformer Language Models such as BERT which obtain excellent results, even matching human performance according to the SQuAD leaderboard.
FrameNet Annotations Alignment using Attention-based Machine Translation
This paper presents an approach to project FrameNet annotations into other languages using attention-based neural machine translation (NMT) models.
Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning
We show that adversarial learning increases all models generalization capabilities both on manual and automatic speech transcription as well as on encyclopedic data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging
Parsing is done recursively, we perform a first inference on the sentence to extract the main scenes and links and then we recursively apply our model on the sentence using a masking feature that reflects the decisions made in previous steps.
Robust Semantic Parsing with Adversarial Learning for Domain Generalization
This paper addresses the issue of generalization for Semantic Parsing in an adversarial framework.
Sources of Complexity in Semantic Frame Parsing for Information Extraction
This paper describes a Semantic Frame parsing System based on sequence labeling methods, precisely BiLSTM models with highway connections, for performing information extraction on a corpus of French encyclopedic history texts annotated according to the Berkeley FrameNet formalism.
Semantic Frame Parsing for Information Extraction : the CALOR corpus
This paper presents a publicly available corpus of French encyclopedic history texts annotated according to the Berkeley FrameNet formalism.
FrameNet automatic analysis : a study on a French corpus of encyclopedic texts
This article presents an automatic frame analysis system evaluated on a corpus of French encyclopedic history texts annotated according to the FrameNet formalism.
Analyse automatique FrameNet : une \'etude sur un corpus fran\ccais de textes encyclop\'ediques (FrameNet automatic analysis : a study on a French corpus of encyclopedic texts)
Cet article pr{\'e}sente un syst{\`e}me d{'}analyse automatique en cadres s{\'e}mantiques {\'e}valu{\'e} sur un corpus de textes encyclop{\'e}diques d{'}histoire annot{\'e}s selon le formalisme FrameNet.
