17 citations · 65 across the 38 of their papers we have counts for
5 papers · 1 filter
Generation or Replication: Auscultating Audio Latent Diffusion Models
Dimitrios Bralios, Gordon Wichern, François G. Germain +4
The introduction of audio latent diffusion models possessing the ability to generate realistic sound clips on demand from a text description has the potential to revolutionize how…
Improving Audio Captioning Models with Fine-grained Audio Features, Text Embedding Supervision, and LLM Mix-up Augmentation
Shih-Lun Wu, Xuankai Chang, Gordon Wichern +4
Automated audio captioning (AAC) aims to generate informative descriptions for various sounds from nature and/or human activities. In recent years, AAC has quickly attracted resear…
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Cinematic Demixing Track
Stefan Uhlich, Giorgio Fabbro, Masato Hirano +14
This paper summarizes the cinematic demixing (CDX) track of the Sound Demixing Challenge 2023 (SDX'23). We provide a comprehensive summary of the challenge setup, detailing the str…
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos
Chiori Hori, Puyuan Peng, David Harwath +7
To realize human-robot collaboration, robots need to execute actions for new tasks according to human instructions given finite prior knowledge. Human experts can share their knowl…
Pac-HuBERT: Self-Supervised Music Source Separation via Primitive Auditory Clustering and Hidden-Unit BERT
Ke Chen, Gordon Wichern, François G. Germain +1
In spite of the progress in music source separation research, the small amount of publicly-available clean source data remains a constant limiting factor for performance. Thus, rec…