Analysing Deep Learning-Spectral Envelope Prediction Methods for Singing Synthesis. - Frederik Bous; Axel Roebel (EUSIPCO, 2019)

Semi-supervised learning of glottal pulse positions in a neural analysis-synthesis framework. - Frederik Bous; Luc Ardaillon; Axel Roebel (EUSIPCO, 2020)

Towards Universal Neural Vocoding with a Multi-band Excited WaveNet. - Axel Roebel; Frederik Bous (CoRR, 2021)

Sequence-To-Sequence Voice Conversion using F0 and Time Conditioning and Adversarial Learning. - Frederik Bous; Laurent Benaroya; Nicolas Obin; Axel Roebel (CoRR, 2021)

Voice Reenactment with F0 and timing constraints and adversarial learning of conversions. - Frederik Bous; Laurent Benaroya; Nicolas Obin; Axel Roebel (EUSIPCO, 2022)

Analysis and transformations of intensity in singing voice. - Frederik Bous; Axel Roebel (CoRR, 2022)

A Bottleneck Auto-Encoder for F0 Transformations on Speech and Singing Voice. - Frederik Bous; Axel Roebel (Inf., 2022)

Neural Vocoding for Singing and Speaking Voices with the Multi-Band Excited WaveNet. - Axel Roebel; Frederik Bous (Inf., 2022)

Analysis and Transformation of Voice Level in Singing Voice. - Frederik Bous; Axel Roebel (ICASSP, 2023)

VaSAB: The variable size adaptive information bottleneck for disentanglement on speech and singing voice. - Frederik Bous; Axel Roebel (CoRR, 2023)

A neural voice transformation framework for modification of pitch and intensity. (Un système neuronal de transformation de la voix pour la modification de la hauteur et de l'intensité). - Frederik Bous (2023)

SupertonicTTS: Towards Highly Scalable and Efficient Text-to-Speech System. - Hyeongju Kim; Jinhyeok Yang; Yechan Yu; Seunghun Ji; Jacob Morton; Frederik Bous; Joon Byun; Juheon Lee (CoRR, 2025)