124 citations · 358 across the 27 of their papers we have counts for
28 papers
Scaffolded Vulnerability: Chatbot-Mediated Reciprocal Self-Disclosure and Need-Supportive Interaction in Couples
Zhuoqun Jiang, ShunYi Yeo, Dorien Herremans +1
While reciprocal self-disclosure drives intimacy, digital tools seldom scaffold autonomy, competence, and relatedness -- the motivational underpinnings defined by Self-Determinatio…
BandCondiNet: Parallel Transformers-based Conditional Popular Music Generation with Multi-View Features
Jing Luo, Xinyu Yang, Dorien Herremans
Conditional music generation offers significant advantages in terms of user convenience and control, presenting great potential in AI-generated content research. However, building…
Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey
Dinh-Viet-Toan Le, Louis Bigo, Mikaela Keller +1
Several adaptations of Transformers models have been developed in various domains since its breakthrough in Natural Language Processing (NLP). This trend has spread into the field…
aiSTROM -- A roadmap for developing a successful AI strategy
Dorien Herremans
A total of 34% of AI research and development projects fails or are abandoned, according to a recent survey by Rackspace Technology of 1,870 companies. We propose a new strategic f…
Underwater Acoustic Communication Receiver Using Deep Belief Network
Abigail Lee-Leon, Chau Yuen, Dorien Herremans
Underwater environments create a challenging channel for communications. In this paper, we design a novel receiver system by exploring the machine learning technique--Deep Belief N…
Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure
Zixun Guo, Makris Dimos, Herremans Dorien
The rise of deep learning technologies has quickly advanced many fields, including that of generative music systems. There exist a number of systems that allow for the generation o…
AttendAffectNet: Self-Attention based Networks for Predicting Affective Responses from Movies
Ha Thi Phuong Thao, Balamurali B. T., Dorien Herremans +1
In this work, we propose different variants of the self-attention based network for emotion prediction from movies, which we call AttendAffectNet. We take both audio and video into…
The Effect of Spectrogram Reconstruction on Automatic Music Transcription: An Alternative Approach to Improve Transcription Accuracy
Kin Wai Cheuk, Yin-Jyun Luo, Emmanouil Benetos +1
Most of the state-of-the-art automatic music transcription (AMT) models break down the main transcription task into sub-tasks such as onset prediction and offset prediction and tra…
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…
Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling
Hao Hao Tan, Dorien Herremans
High-level musical qualities (such as emotion) are often abstract, subjective, and hard to quantify. Given these difficulties, it is not easy to learn good feature representations…
Generative Modelling for Controllable Audio Synthesis of Expressive Piano Performance
Hao Hao Tan, Yin-Jyun Luo, Dorien Herremans
We present a controllable neural audio synthesizer based on Gaussian Mixture Variational Autoencoders (GM-VAE), which can generate realistic piano performances in the audio domain…
PerceptionGAN: Real-world Image Construction from Provided Text through Perceptual Understanding
Kanish Garg, Ajeet kumar Singh, Dorien Herremans +1
Generating an image from a provided descriptive text is quite a challenging task because of the difficulty in incorporating perceptual information (object shapes, colors, and their…
Regression-based music emotion prediction using triplet neural networks
Kin Wai Cheuk, Yin-Jyun Luo, Balamurali B +3
In this paper, we adapt triplet neural networks (TNNs) to a regression task, music emotion prediction. Since TNNs were initially introduced for classification, and not for regressi…
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…
Latent space representation for multi-target speaker detection and identification with a sparse dataset using Triplet neural networks
Kin Wai Cheuk, Balamurali B. T., Gemma Roig +1
We present an approach to tackle the speaker recognition problem using Triplet Neural Networks. Currently, the -vector representation with probabilistic linear discriminant anal…
Midi Miner -- A Python library for tonal tension and track classification
Rui Guo, Dorien Herremans, Thor Magnusson
We present a Python library, called Midi Miner, that can calculate tonal tension and classify different tracks. MIDI (Music Instrument Digital Interface) is a hardware and software…
Multimodal Deep Models for Predicting Affective Responses Evoked by Movies
Ha Thi Phuong Thao, Dorien Herremans, Gemma Roig
The goal of this study is to develop and analyze multimodal models for predicting experienced affective responses of viewers watching movie clips. We develop hybrid multimodal pred…
Doppler Invariant Demodulation for Shallow Water Acoustic Communications Using Deep Belief Networks
Abigail Lee-Leon, Chau Yuen, Dorien Herremans
Shallow water environments create a challenging channel for communications. In this paper, we focus on the challenges posed by the frequency-selective signal distortion called the…
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…
Towards robust audio spoofing detection: a detailed comparison of traditional and learned features
Balamurali BT, Kin Wah Edward Lin, Simon Lui +2
Automatic speaker verification, like every other biometric system, is vulnerable to spoofing attacks. Using only a few minutes of recorded voice of a genuine client of a speaker ve…
Dance Hit Song Prediction
Dorien herremans, David Martens, Kenneth Sörensen
Record companies invest billions of dollars in new talent around the globe each year. Gaining insight into what actually makes a hit song would provide tremendous benefits for the…
MorpheuS: generating structured music with constrained patterns and tension
Dorien Herremans, Elaine Chew
Automatic music generation systems have gained in popularity and sophistication as advances in cloud computing have enabled large-scale complex computations such as deep models and…
A Functional Taxonomy of Music Generation Systems
Dorien Herremans, Ching-Hua Chuan, Elaine Chew
Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical t…