activity
20172023
most citedRDF2PT: Generating Brazilian Portuguese Texts from RDF Data

6 citations · 12 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2023★ 1 cited

A Reference-less Quality Metric for Automatic Speech Recognition via Contrastive-Learning of a Multi-Language Model with Self-Supervision

Kamer Ali Yuksel, Thiago Ferreira, Ahmet Gunduz +2

The common standard for quality evaluation of automatic speech recognition (ASR) systems is reference-based metrics such as the Word Error Rate (WER), computed using manual ground-…

cs.CL2023★ 1 cited

NoRefER: a Referenceless Quality Metric for Automatic Speech Recognition via Semi-Supervised Language Model Fine-Tuning with Contrastive Learning

Kamer Ali Yuksel, Thiago Ferreira, Golara Javadi +2

This paper introduces NoRefER, a novel referenceless quality metric for automatic speech recognition (ASR) systems. Traditional reference-based metrics for evaluating ASR systems r…

cs.CL2022★ 2 cited

Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model

Chris van der Lee, Thiago Castro Ferreira, Chris Emmery +2

This study discusses the effect of semi-supervised learning in combination with pretrained language models for data-to-text generation. It is not known whether semi-supervised lear…

cs.CL2020

NABU Multilingual Graph-based Neural RDF Verbalizer

Diego Moussallem, Dwaraknath Gnaneshwar, Thiago Castro Ferreira +1

The RDF-to-text task has recently gained substantial attention due to continuous growth of Linked Data. In contrast to traditional pipeline models, recent studies have focused on n…

cs.CL2019★ 2 cited

Neural data-to-text generation: A comparison between pipeline and end-to-end architectures

Thiago Castro Ferreira, Chris van der Lee, Emiel van Miltenburg +1

Traditionally, most data-to-text applications have been designed using a modular pipeline architecture, in which non-linguistic input data is converted into natural language throug…

cs.CL2018

NeuralREG: An end-to-end approach to referring expression generation

Thiago Castro Ferreira, Diego Moussallem, Ákos Kádár +2

Traditionally, Referring Expression Generation (REG) models first decide on the form and then on the content of references to discourse entities in text, typically relying on featu…

cs.CL2018★ 6 cited

RDF2PT: Generating Brazilian Portuguese Texts from RDF Data

Diego Moussallem, Thiago Castro Ferreira, Marcos Zampieri +4

The generation of natural language from Resource Description Framework (RDF) data has recently gained significant attention due to the continuous growth of Linked Data. A number of…

cs.CL2017

Trainable Referring Expression Generation using Overspecification Preferences

Thiago castro Ferreira, Ivandre Paraboni

Referring expression generation (REG) models that use speaker-dependent information require a considerable amount of training data produced by every individual speaker, or may othe…