Hou, Yuanbo;
Song, Siyang;
Luo, Cheng;
Mitchell, Andrew;
Ren, Qiaoqiao;
Xie, Weicheng;
Kang, Jian;
... Botteldooren, Dick; + view all
(2023)
Joint Prediction of Audio Event and Annoyance Rating in an Urban Soundscape by Hierarchical Graph Representation Learning.
In:
Proceedings of the INTERSPEECH 2023.
(pp. pp. 331-335).
ISCA: Dublin, Ireland.
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Abstract
Sound events in daily life carry rich information about the objective world. The composition of these sounds affects the mood of people in a soundscape. Most previous approaches only focus on classifying and detecting audio events and scenes, but may ignore their perceptual quality that may impact humans’ listening mood for the environment, e.g. annoyance. To this end, this paper proposes a novel hierarchical graph representation learning (HGRL) approach which links objective audio events (AE) with subjective annoyance ratings (AR) of the soundscape perceived by humans. The hierarchical graph consists of fine-grained event (fAE) embeddings with single-class event semantics, coarse-grained event (cAE) embeddings with multi-class event semantics, and AR embeddings. Experiments show the proposed HGRL successfully integrates AE with AR for AEC and ARP tasks, while coordinating the relations between cAE and fAE and further aligning the two different grains of AE information with the AR.
| Type: | Proceedings paper |
|---|---|
| Title: | Joint Prediction of Audio Event and Annoyance Rating in an Urban Soundscape by Hierarchical Graph Representation Learning |
| Event: | INTERSPEECH 2023 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.21437/Interspeech.2023-1021 |
| Publisher version: | https://doi.org/10.21437/Interspeech.2023-1021 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Hierarchical graph representation learning, audio event classification, human annoyance rating prediction |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10178236 |
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