812 citations · 897 across the 10 of their papers we have counts for
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Exploring the Impact of Noise and Degradations on Heart Sound Classification Models
Davoud Shariat Panah, Andrew Hines, Susan McKeever
The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart s…
Learning Music Representations with wav2vec 2.0
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Learning music representations that are general-purpose offers the flexibility to finetune several downstream tasks using smaller datasets. The wav2vec 2.0 speech representation mo…
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…
More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Non-intrusive speech quality assessment is a crucial operation in multimedia applications. The scarcity of annotated data and the lack of a reference signal represent some of the m…
WARP-Q: Quality Prediction For Generative Neural Speech Codecs
Wissam A. Jassim, Jan Skoglund, Michael Chinen +1
Good speech quality has been achieved using waveform matching and parametric reconstruction coders. Recently developed very low bit rate generative codecs can reconstruct high qual…
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,)…