Abstrakti
Digital audio watermarking consists in inserting a message into audio signals in a transparent way and can be used to allow automatic recognition of audio material and management of the copyrights. We propose a perceptual loss function to be used in deep neural network based audio watermarking systems. The loss is based on the noise-To-mask ratio (NMR), which is a model of the psychoacoustic masking effect characteristic of the human ear. We use the NMR loss between marked and host signals to train the deep neural models and we evaluate the objective quality with PEAQ and the subjective quality with a MUSHRA test.
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | IEEE 5th International Symposium on the Internet of Sounds, IS2 2024 |
| Kustantaja | IEEE |
| Sivumäärä | 6 |
| ISBN (elektroninen) | 9798350366525 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 2024 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | IEEE International Symposium on the Internet of Sounds - Erlangen, Saksa Kesto: 30 syysk. 2024 → 2 lokak. 2024 |
Conference
| Conference | IEEE International Symposium on the Internet of Sounds |
|---|---|
| Maa/Alue | Saksa |
| Kaupunki | Erlangen |
| Ajanjakso | 30/09/24 → 2/10/24 |
Julkaisufoorumi-taso
- Jufo-taso 1
!!ASJC Scopus subject areas
- Music
- Artificial Intelligence
- Computer Networks and Communications
- Hardware and Architecture
- Signal Processing
- Media Technology
Sormenjälki
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