16 citations · 17 across the 6 of their papers we have counts for
6 papers
Beyond Correlation: Evaluating Multimedia Quality Models with the Constrained Concordance Index
Alessandro Ragano, Helard Becerra Martinez, Andrew Hines
This study investigates the evaluation of multimedia quality models, focusing on the inherent uncertainties in subjective Mean Opinion Score (MOS) ratings due to factors like rater…
Dialogue Understandability: Why are we streaming movies with subtitles?
Helard Becerra Martinez, Alessandro Ragano, Diptasree Debnath +4
Watching movies and TV shows with subtitles enabled is not simply down to audibility or speech intelligibility. A variety of evolving factors related to technological advances, cin…
Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction
Helard Becerra, Alessandro Ragano, Andrew Hines
Recent studies have shown how self-supervised models can produce accurate speech quality predictions. Speech representations generated by the pre-trained wav2vec 2.0 model allows c…
A Comparison of Deep Learning MOS Predictors for Speech Synthesis Quality
Alessandro Ragano, Emmanouil Benetos, Michael Chinen +4
Speech synthesis quality prediction has made remarkable progress with the development of supervised and self-supervised learning (SSL) MOS predictors but some aspects related to th…
How deep is your encoder: an analysis of features descriptors for an autoencoder-based audio-visual quality metric
Helard Martinez, Andrew Hines, Mylene C. Q. Farias
The development of audio-visual quality assessment models poses a number of challenges in order to obtain accurate predictions. One of these challenges is the modelling of the comp…
NAViDAd: A No-Reference Audio-Visual Quality Metric Based on a Deep Autoencoder
Helard Martinez, M. C. Farias, A. Hines
The development of models for quality prediction of both audio and video signals is a fairly mature field. But, although several multimodal models have been proposed, the area of a…