7 citations · 21 across the 10 of their papers we have counts for
10 papers
Development and User Experiences of a Novel Virtual Reality Task for Poststroke Visuospatial Neglect: An Exploratory Pilot Study
Andrew Danso, Patti Nijhuis, Alessandro Ansani +10
Background: Visuospatial neglect (VSN) affects spatial awareness, leading to functional and motor challenges. This case study explores virtual reality (VR) as a potential complemen…
Generating Lead Sheets with Affect: A Novel Conditional seq2seq Framework
Dimos Makris, Kat R. Agres, Dorien Herremans
The field of automatic music composition has seen great progress in the last few years, much of which can be attributed to advances in deep neural networks. There are numerous stud…
A dataset and classification model for Malay, Hindi, Tamil and Chinese music
Fajilatun Nahar, Kat Agres, Balamurali BT +1
In this paper we present a new dataset, with musical excepts from the three main ethnic groups in Singapore: Chinese, Malay and Indian (both Hindi and Tamil). We use this new datas…
The impact of Audio input representations on neural network based music transcription
Kin Wai Cheuk, Kat Agres, Dorien Herremans
This paper thoroughly analyses the effect of different input representations on polyphonic multi-instrument music transcription. We use our own GPU based spectrogram extraction too…
nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolution Neural Networks
Kin Wai Cheuk, Hans Anderson, Kat Agres +1
Converting time domain waveforms to frequency domain spectrograms is typically considered to be a prepossessing step done before model training. This approach, however, has several…
Singing Voice Conversion with Disentangled Representations of Singer and Vocal Technique Using Variational Autoencoders
Yin-Jyun Luo, Chin-Chen Hsu, Kat Agres +1
We propose a flexible framework that deals with both singer conversion and singers vocal technique conversion. The proposed model is trained on non-parallel corpora, accommodates m…
Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders
Yin-Jyun Luo, Kat Agres, Dorien Herremans
In this paper, we learn disentangled representations of timbre and pitch for musical instrument sounds. We adapt a framework based on variational autoencoders with Gaussian mixture…
A novel music-based game with motion capture to support cognitive and motor function in the elderly
Kat Agres, Simon Lui, Dorien Herremans
This paper presents a novel game prototype that uses music and motion detection as preventive medicine for the elderly. Given the aging populations around the globe, and the limite…
From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec
Ching-Hua Chuan, Kat Agres, Dorien Herremans
We explore the potential of a popular distributional semantics vector space model, word2vec, for capturing meaningful relationships in ecological (complex polyphonic) music. More p…
From Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models
Carlos Cancino-Chacón, Maarten Grachten, Kat Agres
Tonal structure is in part conveyed by statistical regularities between musical events, and research has shown that computational models reflect tonal structure in music by capturi…