Neural Audio Synthesis for Sound Effects: A Scope Review
Neural Audio Synthesis is dedicated to generating sound through generative neural networks. Sound effects are defined as auditory elements that complement a specific scene (in cinema, fiction, or videogames), support a storyline, enhance a fictional environment, or improve the perceived plausibility and presence (including Virtual Reality) without being music or dialog. This manuscript presents a quantitative literature review of the literature that intersects these two domains: the neural generation of sound effects. By leveraging large language models, we performed an extensive and systematic survey of the major scientific repositories, filtering the most relevant articles to ensure a thorough analysis. Our study examines various generation paradigms employed in sound synthesis, the specific types of sound effects created, the datasets used, and the evaluation metrics considered. Furthermore, we provide a forward-looking discussion on the evolution of this field towards multimodal approaches, where sound generation might integrate with other sensory modalities. All supporting materials and code are available online.
Authors
- Fernando Sánchez Marcos
- Cumhur Erkut (ORCID: https://orcid.org/0000-0003-0750-1919)
- José Luis Blanco
- Mateo Cámara (ORCID: https://orcid.org/0000-0002-1055-6315)
- Anders R. Bargum
- Joshua D. Reiss
Institutions
- Queen Mary University of London (GB)
- European Telecommunications Standards Institute (FR)
- Universidad Politécnica de Madrid (ES)
- Aalborg University (DK)
Publication Details
- Journal
- IEEE Transactions on Audio Speech and Language Processing
- Published
- 2025-12-18
- DOI
- https://doi.org/10.1109/taslpro.2025.3646080
- Primary Topic
- Music Technology and Sound Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- Ministerio de Economía y Competitividad