812 citations · 912 across the 18 of their papers we have counts for
7 papers · 1 filter
ViSQOL v3: An Open Source Production Ready Objective Speech and Audio Metric
Michael Chinen, Felicia S. C. Lim, Jan Skoglund +3
Estimation of perceptual quality in audio and speech is possible using a variety of methods. The combined v3 release of ViSQOL and ViSQOLAudio (for speech and audio, respectively,)…
How Crisp is the Crease? A Subjective Study on Web Browsing Perception of Above-The-Fold
Hamed Z. Jahromi, Declan T. Delaney, Andrew Hines
Quality of Experience (QoE) for various types of websites has gained significant attention in recent years. In order to design and evaluate websites, a metric that can estimate a u…
Speech Quality Factors for Traditional and Neural-Based Low Bit Rate Vocoders
Wissam A. Jassim, Jan Skoglund, Michael Chinen +1
This study compares the performances of different algorithms for coding speech at low bit rates. In addition to widely deployed traditional vocoders, a selection of recently develo…
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…
You Drive Me Crazy! Interactive QoE Assessment for Telepresence Robot Control
Hamed Z. Jahromi, Ivan Bartolec, Edwin Gamboa +2
Telepresence robots (TPRs) are versatile, remotely controlled vehicles that enable physical presence and human-to-human interaction over a distance. Thanks to improving hardware an…
Audio Impairment Recognition Using a Correlation-Based Feature Representation
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Audio impairment recognition is based on finding noise in audio files and categorising the impairment type. Recently, significant performance improvement has been obtained thanks t…
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…