| EPSRC Reference: |
EP/S022694/1 |
| Title: |
UKRI Centre for Doctoral Training in Artificial Intelligence and Music |
| Principal Investigator: |
Dixon, Professor S |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Electronic Eng & Computer Science |
| Organisation: |
Queen Mary University of London |
| Scheme: |
Centre for Doctoral Training |
| Starts: |
01 July 2019 |
Ends: |
31 December 2027 |
Value (£): |
6,532,299
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Composition |
| Human-Computer Interactions |
Music & Acoustic Technology |
| Musicology |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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07 Nov 2018
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UKRI Centres for Doctoral Training AI Interview Panel T – November 2018
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Announced
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Summary on Grant Application Form |
The UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM) will train a new generation of researchers who combine state-of-the-art ability in artificial intelligence (AI), machine learning and signal processing with cross-disciplinary sensibility to deliver groundbreaking original research and impact within the UK Creative Industries (CI) and cultural sector.
The CI sector is a substantial part (5.3%) of the UK's economy and employs more than two million people; it is the fastest growing sector and contributes £92bn of GVA. Bazalgette's "Independent Review of the Creative Industries" highlights their "central importance to the UK's productivity and global success," and notes the particular importance of the music industry, where the UK is one of very few countries who are net exporters.
The need for increasing the scale of doctoral training in AI is clear. The UK government's Industrial Strategy White Paper (2017) identifies the development and maintenance of leading research in AI as the first of four Grand Challenges. To address this challenge, Hall and Pesenti's review recommends support for more PhD places in AI, as does the Royal Society, who noted a "critical need for increased training at PhD level", and a "substantial skills shortage" in Machine Learning (2017).
The core area of this CDT is Music Information Research (MIR, also known as Music Informatics), which involves the use of intelligent information processing methodologies to understand and model music, and to develop products and services for creation, distribution, interaction and experience of music and music-related information. The proposed research focus is structured along three themes identified as requiring intensive attention and integration:
1. Music understanding, encompassing machine listening, intelligent signal processing, and data- and knowledge-driven approaches to music content modelling and analysis;
2. Intelligent instruments and interfaces, encompassing embedded intelligence and intelligent sensing for music performance, production, listening and education, and applications of AI to human-computer interaction in creative contexts;
3. Computational creativity, encompassing generative music composition, automated accompaniment systems, and systems for expressive musical performance and assisted production.
Research in each area will be guided by and grounded in real application needs by a unique set of industrial and cultural stakeholders (see support letters), from big players in media entertainment to innovative SMEs and cultural institutions, encompassing a wide spectrum of the digital music world.
The CDT will take a cohort-based approach, drawing on a supervisory team of over 30 academics led by QMUL's Centre for Digital Music (C4DM), a world-leading research group in the area of music and audio technology with a strong track record in doctoral training. The entire training approach, from the strategic focus to the topics of individual PhD projects, will be guided by C4DM's network of industrial and cultural partners, ranging from large companies and high-profile arts venues to a vibrant network of SMEs including several successful QMUL spin-out companies. Each PhD student will undertake a personalised programme of research supported by specialist taught modules, industrial placements, skills training, and opportunities for co-creation with cultural partners.
The AIM CDT benefits from a substantial institutional investment in the EPSRC and AHRC CDT in Media and Arts Technology (2014-22), for which QMUL has already invested over £6M in specialist facilities, including A/V production studios, a performance laboratory with state-of-the-art motion capture equipment, and specialist maker spaces. AIM builds on QMUL's outstanding track record in this interdisciplinary area, while bringing a new focus to the opportunities and challenges of AI in the creative industries.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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