2 citations · 4 across the 3 of their papers we have counts for
4 papers
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…
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech
Xin Zhang, Iván Vallés-Pérez, Andreas Stolcke +5
Stuttering is a speech disorder where the natural flow of speech is interrupted by blocks, repetitions or prolongations of syllables, words and phrases. The majority of existing au…
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…