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Found 16 papers, 0 papers with code
PE2LGP Animator: A Tool To Animate A Portuguese Sign Language Avatar
Here, we present PE2LGP, an authoring system that features a 3D avatar that signs Portuguese Sign Language.
HamNoSyS2SiGML: Translating HamNoSys Into SiGML
Avatars that can animate sign languages have gained an increase of interest in this area due to their flexibility in the process of generation and edition.
BeamSeg: A Joint Model for Multi-Document Segmentation and Topic Identification
We propose BeamSeg, a joint model for segmentation and topic identification of documents from the same domain.
L2F/INESC-ID at SemEval-2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations
We approach all the subtasks by applying a graph clustering algorithm on contextualized embedding representations of the verbs and arguments.
L2F/INESC-ID at SemEval-2017 Tasks 1 and 2: Lexical and semantic features in word and textual similarity
This paper describes our approach to the SemEval-2017 {``}Semantic Textual Similarity{''} and {``}Multilingual Word Similarity{''} tasks.
Building a Corpus of Errors and Quality in Machine Translation: Experiments on Error Impact
In this paper we describe a corpus of automatic translations annotated with both error type and quality.
JUST.ASK, a QA system that learns to answer new questions from previous interactions
We present JUST. ASK, a publicly available Question Answering system, which is freely available.
Translation errors from English to Portuguese: an annotated corpus
Analysing the translation errors is a task that can help us finding and describing translation problems in greater detail, but can also suggest where the automatic engines should be improved.
Extending a wordnet framework for simplicity and scalability
The WordNet knowledge model is currently implemented in multiple software frameworks providing procedural access to language instances of it.
Dealing with unknown words in statistical machine translation
In Statistical Machine Translation, words that were not seen during training are unknown words, that is, words that the system will not know how to translate.
An English-Portuguese parallel corpus of questions: translation guidelines and application in SMT
Finally, we present a taxonomy of translation errors, according to which we analyze the output of the automatic translation before and after using the corpus as training data.
