Browsing School of Electronic Engineering and Computer Science by Author "Ragano, A"
Now showing items 1-9 of 9
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Adapting the Quality of Experience Framework for Audio Archive Evaluation
Ragano, A; BENETOS, E; Hines, A; 11th International Conference on Quality of Multimedia Experience (11th International Conference on Quality of Multimedia Experience, 2019-06-05)Perceived quality of historical audio material that is subjected to digitisation and restoration is typically evaluated by individual judgements or with inappropriate objective quality models. This paper presents a Quality ... -
Audio impairment recognition using a correlation-based feature representation
Ragano, A; Benetos, E; Hines, A; 12th International Conference on Quality of Multimedia Experience (QoMEX) (IEEE, 2020-05-26)Audio impairment recognition is based on finding noise in audio files and categorising the impairment type. Recently, significant performance improvement has been obtained thanks to the usage of advanced deep learning ... -
Audio Quality Assessment of Vinyl Music Collections Using Self-Supervised Learning
Ragano, A; Benetos, E; Hines, A; 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2023-06-04)Metadata such as mean opinion score (MOS) quality ratings are critical to improve the usability and accessibility of music archive collections. Developing a non-intrusive objective quality metric that predicts MOS of archive ... -
Automatic Quality Assessment of Digitized and Restored Sound Archives
Ragano, A; Benetos, E; Hines, A (2022) -
A Comparison Of Deep Learning MOS Predictors For Speech Synthesis Quality
Ragano, A; Benetos, E; Chinen, M; Martinez, HB; Reddy, CKA; Skoglund, J; Hines, A (2023) -
Development of a Speech Quality Database Under Uncontrolled Conditions
Ragano, A; Benetos, E; Hines, A; 21st Annual Conference of the International Speech Communication Association (INTERSPEECH 2020) (2020-10-25)Objective audio quality assessment is preferred to avoid time-consuming and costly listening tests. The development of objective quality metrics depends on the availability of datasets appropriate to the application under ... -
Learning Music Representations with wav2vec 2.0
Ragano, A; Benetos, E; Hines, A; 31st Irish Conference on Artificial Intelligence and Cognitive Science (AICS) (IEEE, 2023-12-07)Learning music representations that are general- purpose offers the flexibility to finetune several downstream tasks using smaller datasets. The wav2vec 2.0 speech representation model showed promising results in many ... -
Measuring National Mood with Music: Using Machine Learning to Construct a Measure of National Valence from Audio Data
Benetos, E; Ragano, A; Sgroi, D; Tuckwell, AWe propose a new measure of national valence based on the emotional content of a country’s most popular songs. We first trained a machine learning model using 191 different audio features embedded within music and use this ... -
More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations
Ragano, A; Benetos, E; Hines, A; 13th International Conference on Quality of Multimedia Experience (QoMEX) (QoMEX, 2021-06-14)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 main challenges for designing efficient ...