Search Results for author:
Found 16 papers, 5 papers with code
PeLLE: Encoder-based language models for Brazilian Portuguese based on open data
In this paper we present PeLLE, a family of large language models based on the RoBERTa architecture, for Brazilian Portuguese, trained on curated, open data from the Carolina corpus.
Acoustic models of Brazilian Portuguese Speech based on Neural Transformers
In this work, we build an acoustic model of Brazilian Portuguese Speech through a Transformer neural network.
Carolina: a General Corpus of Contemporary Brazilian Portuguese with Provenance, Typology and Versioning Information
This paper presents the first publicly available version of the Carolina Corpus and discusses its future directions.
Interpretability Analysis of Deep Models for COVID-19 Detection
During the outbreak of COVID-19 pandemic, several research areas joined efforts to mitigate the damages caused by SARS-CoV-2.
Pretrained audio neural networks for Speech emotion recognition in Portuguese
This dataset contains about $50$ minutes of Brazilian Portuguese speech.
Audio MFCC-gram Transformers for respiratory insufficiency detection in COVID-19
This work explores speech as a biomarker and investigates the detection of respiratory insufficiency (RI) by analyzing speech samples.
Combined Learning of Neural Network Weights for Privacy in Collaborative Tasks
With CoLN, local hosts use the same Neural Network architecture and base parameters to train a model using only locally available data.
verBERT: Automating Brazilian Case Law Document Multi-label Categorization Using BERT
In this work, we carried out a study about the use of attention-based algorithms to automate the categorization of Brazilian case law documents.
Text-to-hashtag Generation using Seq2seq Learning
We concluded that the texts predicted by the neural networks are very promising for use as hashtags for products on Ecommerce websites.
Extending Description Logic EL++ with Linear Constraints on the Probability of Axioms
We show that the consistency detection problem for such a probabilistic description logic is NP-complete, and present a linear algebraic deterministic algorithm to solve it, using the column generation technique.
Quantitative Logic Reasoning
In this paper we show several similarities among logic systems that deal simultaneously with deductive and quantitative inference.
A logical-based corpus for cross-lingual evaluation
At present, different deep learning models are presenting high accuracy on popular inference datasets such as SNLI, MNLI, and SciTail.
Semantic Parsing: Syntactic assurance to target sentence using LSTM Encoder CFG-Decoder
Semantic parsing can be defined as the process of mapping natural language sentences into a machine interpretable, formal representation of its meaning.
Semantic Parsing Natural Language into SPARQL: Improving Target Language Representation with Neural Attention
Semantic parsing is the process of mapping a natural language sentence into a formal representation of its meaning.
