Daniel Saez-Trigueros

According to our database, Daniel Saez-Trigueros authored at least 11 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Enhancing the Stability of LLM-based Speech Generation Systems through Self-Supervised Representations.

Álvaro Martín-Cortinas, Daniel Sáez-Trigueros, Iván Vallés-Pérez, Biel Tura Vecino, Piotr Bilinski, Mateusz Lajszczak, Grzegorz Beringer, Roberto Barra-Chicote, Jaime Lorenzo-Trueba

CoRR, 2024

2023

Sign Language Motion Generation from Sign Characteristics.

Manuel Gil-Martín, María Villa-Monedero, Andrzej Pomirski, Daniel Sáez-Trigueros, Rubén San Segundo

Sensors, December, 2023

Sign Language Dataset for Automatic Motion Generation.

María Villa-Monedero, Manuel Gil-Martín, Daniel Sáez-Trigueros, Andrzej Pomirski, Rubén San Segundo

J. Imaging, 2023

2022

GlowVC: Mel-spectrogram space disentangling model for language-independent text-free voice conversion.

Magdalena Proszewska, Grzegorz Beringer, Daniel Sáez-Trigueros, Thomas Merritt, Abdelhamid Ezzerg, Roberto Barra-Chicote

Proceedings of the Interspeech 2022, 2022

2021

Generating photo-realistic training data to improve face recognition accuracy.

Daniel Saez-Trigueros, Li Meng, Margaret Hartnett

Neural Networks, 2021

Enhancing audio quality for expressive Neural Text-to-Speech.

Abdelhamid Ezzerg, Adam Gabrys, Bartosz Putrycz, Daniel Korzekwa, Daniel Saez-Trigueros, David McHardy, Kamil Pokora, Jakub Lachowicz, Jaime Lorenzo-Trueba, Viacheslav Klimkov

CoRR, 2021

2020

CopyCat: Many-to-Many Fine-Grained Prosody Transfer for Neural Text-to-Speech.

Sri Karlapati, Alexis Moinet, Arnaud Joly, Viacheslav Klimkov, Daniel Sáez-Trigueros, Thomas Drugman

Proceedings of the Interspeech 2020, 2020

2019

Design and real-world application of novel machine learning techniques for improving face recognition algorithms.

Daniel Sáez-Trigueros

PhD thesis, 2019

2018

Enhancing convolutional neural networks for face recognition with occlusion maps and batch triplet loss.

Daniel Saez-Trigueros, Li Meng, Margaret Hartnett

Image Vis. Comput., 2018

Face Recognition: From Traditional to Deep Learning Methods.

Daniel Saez-Trigueros, Li Meng, Margaret Hartnett

CoRR, 2018

2016

Shape and texture combined face recognition for detection of forged ID documents.

Daniel Saez-Trigueros, Heinz Hertlein, Li Meng, Margaret Hartnett

Proceedings of the 39th International Convention on Information and Communication Technology, 2016