People

spatial and immersive audio, music signal processing, machine learning for audio, music information retrieval

new interfaces for musical expression, augmented instruments, performance study, human-computer interaction, embedded hardware

new interfaces for musical expression, performance study, human-computer interaction, interaction design

Communication acoustics, crossmodal correspondences, sound synthesis, cognitive audio, musical haptics

Machine listening, music information retrieval, computational sound scene analysis, machine learning for audio analysis, language models for music and audio, computational musicology

Semantic Audio, Music Information Retrieval, Semantic Web for Music, Machine Learning and Data Science, Music Emotion Recognition, Interactive music sytems (e.g. intellignet editing, audio production and performance systems)

automatic music labelling, music information retrieval, music signal processing, machine learning for audio, chord/key/structure (joint) estimation, instrument identification, multi-track/channel audio, music transcription, graphical models, big data science

sound engineering, intelligent audio production, sound synthesis, audio effects, automatic mixing

signal processing; machine learning; robot perception

Digital Signal Processing, Digital Audio, Music Informatics, Audio Features, Semantic Audio, Immersive Audio, Studio Science, Music Data Science, Music Linked Data.

Music information research, Internet of musical things, Extended reality, New interfaces for musical expression, Semantic audio, Music perception (timbre, emotions), Audience-Performer interaction, Participatory art

Music informatics, music signal processing, artificial intelligence, music cognition; extraction of musical content (e.g. rhythm, harmony, intonation) from audio signals: beat tracking, audio alignment, chord and note transcription, singing intonation; using signal processing approaches, probabilistic models, and deep learning.

Interaction Design, auditory displays, Data Sonification, Collaborative Systems, Cross-modal Interaction, Assistive Technology, Accessibility

Computational Creativity, Artificial Intelligence, Music Cognition

Music Cognition, Auditory Perception, Empirical Aesthetics, Statistical Learning, Probabilistic Modelling.

computational linguistics including models of language and music

description

: Probabilistic learning of sequential structures in music cognition

Beyond the fret: gesture analysis on fretted instruments and its applications to instrument augmentation

Self-supervision in Audio Fingerprinting

User-driven deep music generation in digital audio workstations

Design for auditory imagery

Real-Time Gesture Classification on an Augmented Acoustic Guitar using Deep Learning to Improve Extended-Range and Percussive Solo Playing

Deep Learning for Jazz Piano: Transcription + Generative Modeling

Computational analysis of chick vocalisations: from categorisation to live feedback

Latent Spaces for Human-AI music generation

Perceptually motivated deep learning approaches to creative sound synthesis

Towards Composing Contemporary Classical Music using Generative Deep Learning

The Sound of Care: researching the use of Deep Learning and Sonification for the daily support of people with Chronic Primary Pain

Singing Voice Attribute Transformation

Cover Song Identification

Leveraging cross-sensory associations in communication

Neural Audio Synthesis with Expressiveness Control

End-to-end generative modeling of multitrack mixing with non-parallel data and adversarial networks

Perceptual end to end learning for music understanding

Audio Source Separation for Advanced Digital Audio Effects

Modelling the Creative Process of Jazz Improvisation

Machine Learning of Physical Models for Voice Synthesis

Automatic micro-composition for professional/novice composers using generative models as creativity support tools

Co-creative Algorithmic Composition Based on Models of Affective Response

Optical music recognition using deep learning

Artificial Intelligence for Supporting Musical Creativity and Engagement in Child-Computer Interaction

The role of nostalga in music production

Exploring the role of culture and community in the design of new musical instruments

Informed source separation for multi-mic production

Computational Modelling of Expressive Piano Performance

Semantic understanding of TV programme content and structure to enable automatic enhancement and adjustment

Multimodal Deep Learning for Music Information Retrieval

AI for everyday sounds

Real-time timbral mapping for synthesized percussive performance

Automatic music transcription with end-to-end deep neural networks

Meta-Physical Modelling

Gender-coded sound: A multimodal data-driven analysis of gender encoding strategies in sound and music for advertising

Improving AI-generated Music with Pleasure Models

Machine learning applied to sound synthesis models

Music emotion modelling using graph analysis

Deep Learning methods for Multi-Instrument Music Transcription

PERFORM-AI (Provide Extended Realities for Musical Performance using AI)

An investigation evaluating realism in sound design

Generative Models For Music Audio Representation And Understanding

E-AIM - Embodied Cognition in Intelligent Musical Systems

Guitar-Oriented Neural Music Generation in Symbolic Format

Sensor mesh as performance interface

Continuous mood recognition in film music

New perspectives in instrument-based audio source separation

Physiological Responses to Ensemble Interaction

Style classification of podcasts using audio

Audio Applications of Novel Mathematical Methods in Deep Learning

Music Production Style Transfer and Mix Similarity

Sabotaging, errors and other mistakes as a source of new techniques in music improvisation

Probabilistic modelling of rhythm perception and production

Expressive Performance Rendering for Music Generation Systems

Predicting demographics, personalities, and global values from digital media behaviours

Pitch tracking for music applications - beyond 99% accuracy

Active Learning for Interactive Music Transcription

Self-supervision in machine listening

Industry-scale Machine Listening for Music and Audio Data

Machine Learning Methods for Artificial Musicality

Computational Comparison Between Different Genres of Music in Terms of the Singing Voice

Representation Learning for Audio Production Style and Modulations

Music Interestingness in the Brain

Networks able to display relationships between human and nonhuman actors. Project: Sensing the Forest.

Project: Digital Platforms for Craft in the UK and China

Deep learning technologies for multi-instrument automatic music transcription

Projects: UKRI Centre for Doctoral Training in Artificial Intelligence and Music, New Frontiers in Music Information Processing (MIP-Frontiers)

Project: Centre for Doctoral Training in Media and Arts Technology

Automated Music Performance Assessment and Critique

Deep learning, representation learning, bioacoustics

music transcription (chords, beats, drums, melody, ...), interactive music annotation, singing research, research in the evolution of musical styles