On 14-19 April, several AIM researchers will participate at the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024). ICASSP is the leading conference in the field of signal processing and the flagship event of the IEEE Signal Processing Society.As in previous years, the UKRI Centre for Doctoral Training in AI and Music will have a strong presence at the conference, both in terms of numbers and overall impact. The below papers presented at ICASSP 2024 are authored or co-authored by AIM students:
- High resolution guitar transcription via domain adaptation, by Xavier Riley, Drew Edwards, and Simon Dixon
- Bass accompaniment generation via latent diffusion, by Marco Pasini, Maarten Grachten, and Stefan Lattner
- Unsupervised pitch-timbre disentanglement of musical instruments using a Jacobian disentangled sequential autoencoder, by Yin-Jyun Luo, Sebastian Ewert, and Simon Dixon
- Posterior variance-parameterised Gaussian dropout: improving disentangled sequential autoencoders for zero-shot voice conversion, by Yin-Jyun Luo and Simon Dixon
- Mertech: instrument playing technique detection using self-supervised pretrained model with multi-task finetuning, by Dichucheng Li, Yinghao Ma, Weixing Wei, Qiuqiang Kong, Yulun Wu, Mingjin Che, Fan Xia, Emmanouil Benetos, and Wei Li
- Syncfusion: Multimodal Onset-Synchronized Video-to-Audio Foley Synthesis, by Marco Comunità, Riccardo F. Gramaccioni, Emilian Postolache, Emanuele Rodolà, Danilo Comminiello, and Joshua D. Reiss
The following paper will be presented at the ICASSP Workshop on Explainable Machine Learning for Speech and Audio:
- Explainable modeling of gender-targeting practices in toy advertising sound and music, by Luca Marinelli and Charalampos Saitis
See you all at ICASSP!