activity
20172024
most citedMore for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations

14 citations · 54 across the 17 of their papers we have counts for

collaborators

28 papers

eess.AS2021

An evaluation of data augmentation methods for sound scene geotagging

Helen L. Bear, Veronica Morfi, Emmanouil Benetos

Sound scene geotagging is a new topic of research which has evolved from acoustic scene classification. It is motivated by the idea of audio surveillance. Not content with only des…

eess.AS2021

Joint Scattering for Automatic Chick Call Recognition

Changhong Wang, Emmanouil Benetos, Shuge Wang +1

Animal vocalisations contain important information about health, emotional state, and behaviour, thus can be potentially used for animal welfare monitoring. Motivated by the spectr…

eess.AS202114 cited

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…

cs.SD20212 cited

Pitch-Informed Instrument Assignment Using a Deep Convolutional Network with Multiple Kernel Shapes

Carlos Lordelo, Emmanouil Benetos, Simon Dixon +1

This paper proposes a deep convolutional neural network for performing note-level instrument assignment. Given a polyphonic multi-instrumental music signal along with its ground tr…

cs.SD2021

Revisiting the Onsets and Frames Model with Additive Attention

Kin Wai Cheuk, Yin-Jyun Luo, Emmanouil Benetos +1

Recent advances in automatic music transcription (AMT) have achieved highly accurate polyphonic piano transcription results by incorporating onset and offset detection. The existin…

cs.SD20219 cited

Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation

Carlos Lordelo, Emmanouil Benetos, Simon Dixon +2

This paper addresses the problem of domain adaptation for the task of music source separation. Using datasets from two different domains, we compare the performance of a deep learn…