Uncategorised – UKRI Centre for Doctoral Training in Artificial Intelligence and Music

Christos Plachouras
26th July 2024

CfP: First AES International Conference on AI and Machine Learning for Audio (AIMLA 2025)

First AES International Conference on Artificial Intelligence and Machine Learning for Audio (AIMLA 2025), Queen Mary University of London, Sept. 8-10, 2025, Call for contributions

The Audio Engineering Society and the Centre for Digital Music invite audio researchers and practitioners, from academia and industry to participate in the first AES conference dedicated to artificial intelligence and machine learning, as it applies to audio. This 3 day event, aims to bring the community together, educate, demonstrate and advance the state of the art. It will feature keynote speakers, workshops, tutorials, challenges and cutting-edge peer-reviewed research.

The scope is wide – expecting attendance from all types of institutions, including academia, industry, and pure research, with diverse disciplinary perspectives – but tied together by a focus on artificial intelligence and machine learning for audio.

For more information on the Calls for Papers, Special Sessions, Tutorials, and Challenges, please visit the conference website.

Three AIM PhD students are part of the organising committee, with Soumya Sai Vanka and Franco Caspe serving as Special Sessions Co-Chairs, and Farida Yusuf serving as Sponsorship Chair.

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Yazhou Li
27th November 2023

AIM at NeurIPS 2023

On 10-16 December, several AIM researchers will participate at the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), taking place in New Orleans, USA. NeurIPS is a world-leading conference in AI, machine learning, and computational neuroscience, attracting more than ten thousand attendees annually. The AI and Music centre for doctoral training will have a strong presence at NeurIPS 2023.

In the Main Conference and specifically its Datasets and Benchmarks track, the following paper is authored by AIM members:

MARBLE: Music Audio Representation Benchmark for Universal Evaluation (Ruibin Yuan, Yinghao Ma, Yizhi Li, Ge Zhang, Xingran Chen, Hanzhi Yin, Zhuo Le, Yiqi Liu, Jiawen Huang, Zeyue Tian, Binyue Deng, Ningzhi Wang, Chenghua Lin, Emmanouil Benetos, Anton Ragni, Norbert Gyenge, Roger Dannenberg, Wenhu Chen, Gus Xia, Wei Xue, Si Liu, Shi Wang, Ruibo Liu, Yike Guo, Jie Fu)

In the NeurIPS Machine Learning for Audio Workshop:

AIM PhD student Ben Hayes is giving an invited talk on Differentiable digital signal processing (DDSP).

And the following papers are authored by AIM members:

The Song Describer dataset: a corpus of audio captions for music-and-language evaluation (Ilaria Manco, Benno Weck, SeungHeon Doh, Minz Won, Yixiao Zhang, Dmitry Bodganov, Yusong Wu, Ke Chen, Philip Tovstogan, Emmanouil Benetos, Elio Quinton, George Fazekas, Juhan Nam)
Self-Supervised Music Source Separation Using Vector-Quantized Source Category Estimates (Marco Pasini, Stefan Lattner, George Fazekas)

See you at NeurIPS!

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Emmanouil Benetos
30th October 2023

WASPAA 2023 paper awards for AIM

The 2023 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics has just taken place, and we are please to announce that the following paper awards were given to AIM students:

AIM PhD student Saurjya Sarkar has been given the Best Student Paper Award for the paper titled “Leveraging synthetic data for improving chamber ensemble separation” – you can read a postprint at: https://qmro.qmul.ac.uk/xmlui/handle/123456789/89844
AIM PhD student Christian Steinmetz has been given the Best Paper Award for the paper titled “General Purpose Audio Effect Removal” – you can read a postprint at: https://qmro.qmul.ac.uk/xmlui/handle/123456789/91026

Congratulations to all! You can explore AIM’s contributions for WASPAA 2023 at: https://www.aim.qmul.ac.uk/aim-at-waspaa-2023/

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