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Learning affective correspondence between music and image
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Verma, Gaurav , Dhekane , Eeshan G. and Guha, Tanaya (2019) Learning affective correspondence between music and image. In: International Conference on Acoustics, Speech and Signal Processing (ICASSP, Brighton, 12-17 May 2019. Published in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) doi:10.1109/ICASSP.2019.8683133 ISSN 2379-190X.
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WRAP-learning-affective-correspondence-music-image-Guha-2019.pdf - Accepted Version - Requires a PDF viewer. Download (2798Kb) | Preview |
Official URL: https://doi.org/10.1109/ICASSP.2019.8683133
Abstract
We introduce the problem of learning affective correspondence between audio (music) and visual data (images). For this task, a music clip and an image are considered similar (having true correspondence) if they have similar emotion content. In order to estimate this cross modal, emotion-centric similarity, we propose a deep neural network architecture that learns to project the data from the two modalities to a common representation space, and performs a binary classification task of predicting the affective correspondence (true or false). To facilitate the current study, we construct a large scale database containing more than 3,500 music clips and 85,000 images with three emotion classes (positive, neutral, negative). The proposed approach achieves 61.67%accuracy for the affective correspondence prediction task on this database, outperforming two relevant and competitive baselines. We also demonstrate that our net-work learns modality-specific representations of emotion (without explicitly being trained with emotion labels), which are useful foremotion recognition in individual modalities.
| Item Type: | Conference Item (Paper) | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology | ||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Music -- Psychological aspects, Imagery (Psychology) | ||||||
| Journal or Publication Title: | ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | ||||||
| Publisher: | IEEE | ||||||
| ISSN: | 2379-190X | ||||||
| Official Date: | 17 April 2019 | ||||||
| Dates: |
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| DOI: | 10.1109/ICASSP.2019.8683133 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 19 February 2019 | ||||||
| Date of first compliant Open Access: | 19 February 2019 | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | International Conference on Acoustics, Speech and Signal Processing (ICASSP | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Brighton | ||||||
| Date(s) of Event: | 12-17 May 2019 | ||||||
| Related URLs: |
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