16 citations · 17 across the 2 of their papers we have counts for
3 papers
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…
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…