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2020 – today
- 2024
[c8]Guillermo Cámbara, Patrick Lumban Tobing, Mikolaj Babianski, Ravichander Vipperla, Duo Wang, Ron Shmelkin, Giuseppe Coccia, Orazio Angelini, Arnaud Joly, Mateusz Lajszczak, Vincent Pollet:
Mapache: Masked Parallel Transformer for Advanced Speech Editing and Synthesis. ICASSP 2024: 10691-10695- [i9]Álvaro Martín-Cortinas, Daniel Sáez-Trigueros, Iván Vallés-Pérez, Biel Tura Vecino, Piotr Bilinski, Mateusz Lajszczak, Grzegorz Beringer, Roberto Barra-Chicote, Jaime Lorenzo-Trueba:
Enhancing the Stability of LLM-based Speech Generation Systems through Self-Supervised Representations. CoRR abs/2402.03407 (2024) - [i8]Mateusz Lajszczak, Guillermo Cámbara, Yang Li, Fatih Beyhan, Arent van Korlaar, Fan Yang, Arnaud Joly, Álvaro Martín-Cortinas, Ammar Abbas, Adam Michalski, Alexis Moinet, Sri Karlapati, Ewa Muszynska, Haohan Guo, Bartosz Putrycz, Soledad López Gambino, Kayeon Yoo, Elena Sokolova, Thomas Drugman:
BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data. CoRR abs/2402.08093 (2024) - 2023
- [c7]Arnaud Joly, Marco Nicolis, Ekaterina Peterova, Alessandro Lombardi, Ammar Abbas, Arent van Korlaar, Aman Hussain, Parul Sharma, Alexis Moinet, Mateusz Lajszczak, Penny Karanasou, Antonio Bonafonte, Thomas Drugman, Elena Sokolova:
Controllable Emphasis with zero data for text-to-speech. SSW 2023: 113-119 - [i7]Arnaud Joly, Marco Nicolis, Ekaterina Peterova, Alessandro Lombardi, Ammar Abbas, Arent van Korlaar, Aman Hussain, Parul Sharma, Alexis Moinet, Mateusz Lajszczak, Penny Karanasou, Antonio Bonafonte, Thomas Drugman, Elena Sokolova:
Controllable Emphasis with zero data for text-to-speech. CoRR abs/2307.07062 (2023) - 2022
- [c6]Marek Strelec, Jonas Rohnke, Antonio Bonafonte, Mateusz Lajszczak, Trevor Wood:
Discrete Acoustic Space for an Efficient Sampling in Neural Text-To-Speech. IberSPEECH 2022: 1-5 - [c5]Mateusz Lajszczak, Animesh Prasad, Arent van Korlaar, Bajibabu Bollepalli, Antonio Bonafonte, Arnaud Joly, Marco Nicolis, Alexis Moinet, Thomas Drugman, Trevor Wood, Elena Sokolova:
Distribution Augmentation for Low-Resource Expressive Text-To-Speech. ICASSP 2022: 8307-8311 - [c4]Sri Karlapati, Penny Karanasou, Mateusz Lajszczak, Syed Ammar Abbas, Alexis Moinet, Peter Makarov, Ray Li, Arent van Korlaar, Simon Slangen, Thomas Drugman:
CopyCat2: A Single Model for Multi-Speaker TTS and Many-to-Many Fine-Grained Prosody Transfer. INTERSPEECH 2022: 3363-3367 - [c3]Peter Makarov, Syed Ammar Abbas, Mateusz Lajszczak, Arnaud Joly, Sri Karlapati, Alexis Moinet, Thomas Drugman, Penny Karanasou:
Simple and Effective Multi-sentence TTS with Expressive and Coherent Prosody. INTERSPEECH 2022: 3368-3372 - [i6]Mateusz Lajszczak, Animesh Prasad, Arent van Korlaar, Bajibabu Bollepalli, Antonio Bonafonte, Arnaud Joly, Marco Nicolis, Alexis Moinet, Thomas Drugman, Trevor Wood, Elena Sokolova:
Distribution augmentation for low-resource expressive text-to-speech. CoRR abs/2202.06409 (2022) - [i5]Sri Karlapati, Penny Karanasou, Mateusz Lajszczak, Ammar Abbas, Alexis Moinet, Peter Makarov, Ray Li, Arent van Korlaar, Simon Slangen, Thomas Drugman:
CopyCat2: A Single Model for Multi-Speaker TTS and Many-to-Many Fine-Grained Prosody Transfer. CoRR abs/2206.13443 (2022) - [i4]Peter Makarov, Ammar Abbas, Mateusz Lajszczak, Arnaud Joly, Sri Karlapati, Alexis Moinet, Thomas Drugman, Penny Karanasou:
Simple and Effective Multi-sentence TTS with Expressive and Coherent Prosody. CoRR abs/2206.14643 (2022) - 2021
- [i3]Marek Strelec, Jonas Rohnke, Antonio Bonafonte, Mateusz Lajszczak, Trevor Wood:
Discrete acoustic space for an efficient sampling in neural text-to-speech. CoRR abs/2110.12539 (2021)
2010 – 2019
- 2019
- [c2]Daniel Korzekwa
, Roberto Barra-Chicote, Bozena Kostek, Thomas Drugman, Mateusz Lajszczak:
Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech. INTERSPEECH 2019: 3890-3894 - [c1]Nishant Prateek, Mateusz Lajszczak, Roberto Barra-Chicote, Thomas Drugman, Jaime Lorenzo-Trueba, Thomas Merritt, Srikanth Ronanki, Trevor Wood:
In Other News: a Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data. NAACL-HLT (2) 2019: 205-213 - [i2]Nishant Prateek, Mateusz Lajszczak, Roberto Barra-Chicote, Thomas Drugman, Jaime Lorenzo-Trueba, Thomas Merritt, Srikanth Ronanki, Trevor Wood:
In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data. CoRR abs/1904.02790 (2019) - [i1]Daniel Korzekwa, Roberto Barra-Chicote, Bozena Kostek, Thomas Drugman, Mateusz Lajszczak:
Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech. CoRR abs/1907.04743 (2019)
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