Towards the Synthesis of Non-speech Vocalizations
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Abstract (arXiv)
In this report, we focus on the unconditional generation of infant cry sounds using the DiffWave framework, which has shown great promise in generating high-quality audio from noise. We use two distinct datasets of infant cries: the Baby Chillanto and the deBarbaro cry dataset. These datasets are used to train the DiffWave model to generate new cry sounds that maintain high fidelity and diversity. The focus here is on DiffWave's capability to handle the unconditional generation task.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 5 references that are in the map. First posted on arXiv 12 Oct 2024.
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3 of 5 references.
References · 3
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
- 2020Infant Crying Detection in Real-World Environmentscited by 5
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