124 citations · 315 across the 16 of their papers we have counts for
24 papers
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…