@conference {2021,
	title = {Sen2Seq: A Conditional seq2seq Framework for Generating Lead Sheets with Sentiment},
	booktitle = {Proceedings of the International Joint Conference on Neural Networks (IJCNN)},
	year = {2021},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Virtual},
	author = {Dimos Makris and Kat Agres and D Herremans}
}
@conference {2020,
	title = {Singing Voice Conversion with Disentangled Representations of Singer and Vocal Technique Using Variational Autoencoders},
	booktitle = {45th International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP 2020)},
	year = {2020},
	abstract = {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 many-to-many conversion, and leverages recent advances of variational autoencoders. It employs separate encoders to learn disentangled latent representations of singer identity and vocal technique separately, with a joint decoder for reconstruction. Conversion is carried out by simple vector arithmetic in the learned latent spaces. Both a quantitative analysis as well as a visualization of the converted spectrograms show that our model is able to disentangle singer identity and vocal technique and successfully perform conversion of these attributes. To the best of our knowledge, this is the first work to jointly tackle conversion of singer identity and vocal technique based on a deep learning approach.},
	author = {Yin-Jyun Luo and Chin-Cheng Hsu and Kat Agres and Dorien Herremans}
}
@conference {2018,
	title = {The Structure of Chord Progressions Influences Listeners{\textquoteright} Enjoyment and Absorptive States in EDM},
	booktitle = {International Conference on Music Perception and Cognition},
	year = {2018},
	address = {Sydney, Australia},
	abstract = {The field of music cognition has given comparatively little consideration to the topic of altered listening states, such as audience flow, trancing, and absorptive states. Some research has investigated the relationship between musical features (such as repetitiveness or information-theoretic characteristics) and enjoyment of the music, but the impact of musical structure on absorptive states has yet to be thoroughly addressed. The present study sought to fill this gap in the literature by examining harmonic structure, enjoyment, and absorptive listening states in Uplifting Trance (UT), a sub-genre of Electronic Dance Music (EDM). Rather than examine the obvious (and previously considered) connection between driving rhythmic cues and absorptive listening states, we aimed to investigate the effect of harmonic repetition on listening states. Based on previous work (Agres, et al, 2017), we generated a number of UT excerpts with varying degrees of harmonic repetition. These excerpts were used in an online listening task with 19 experienced trance/EDM listeners. We discovered that chord progressions significantly influenced both listeners{\textquoteright} enjoyment of the music as well as their reported absorptive listening states. Overall, the results from this study indicate that moderately complex chord sequences elicit greater enjoyment than very repetitive chord sequences or sequences that violate listeners{\textquoteright} expectations. A significant correlation between highly enjoyed sequences and absorptive listening states was also observed.},
	author = {Kat Agres and Dorien Herremans}
}
