1 citations · 2 across the 5 of their papers we have counts for
6 papers
Investigating self-supervised features for expressive, multilingual voice conversion
Álvaro Martín-Cortinas, Daniel Sáez-Trigueros, Grzegorz Beringer +7
Voice conversion (VC) systems are widely used for several applications, from speaker anonymisation to personalised speech synthesis. Supervised approaches learn a mapping between d…
Enhancing the Stability of LLM-based Speech Generation Systems through Self-Supervised Representations
Álvaro Martín-Cortinas, Daniel Sáez-Trigueros, Iván Vallés-Pérez +6
Large Language Models (LLMs) are one of the most promising technologies for the next era of speech generation systems, due to their scalability and in-context learning capabilities…
SCRAPS: Speech Contrastive Representations of Acoustic and Phonetic Spaces
Ivan Vallés-Pérez, Grzegorz Beringer, Piotr Bilinski +2
Numerous examples in the literature proved that deep learning models have the ability to work well with multimodal data. Recently, CLIP has enabled deep learning systems to learn s…
GlowVC: Mel-spectrogram space disentangling model for language-independent text-free voice conversion
Magdalena Proszewska, Grzegorz Beringer, Daniel Sáez-Trigueros +3
In this paper, we propose GlowVC: a multilingual multi-speaker flow-based model for language-independent text-free voice conversion. We build on Glow-TTS, which provides an archite…
Improving multi-speaker TTS prosody variance with a residual encoder and normalizing flows
Iván Vallés-Pérez, Julian Roth, Grzegorz Beringer +2
Text-to-speech systems recently achieved almost indistinguishable quality from human speech. However, the prosody of those systems is generally flatter than natural speech, produci…
Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
Daniel Korzekwa, Roberto Barra-Chicote, Szymon Zaporowski +6
This paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction an…