Controllable Emphasis with zero data for text-to-speech

no code implementations • 13 Jul 2023 • 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

We show that this technique significantly closes the gap to methods that require explicit recordings.

Sentence Text to Speech

Distribution augmentation for low-resource expressive text-to-speech

no code implementations • 13 Feb 2022 • Mateusz Lajszczak, Animesh Prasad, Arent van Korlaar, Bajibabu Bollepalli, Antonio Bonafonte, Arnaud Joly, Marco Nicolis, Alexis Moinet, Thomas Drugman, Trevor Wood, Elena Sokolova

This paper presents a novel data augmentation technique for text-to-speech (TTS), that allows to generate new (text, audio) training examples without requiring any additional data.

Data Augmentation Diversity +1

Dynamic Prosody Generation for Speech Synthesis using Linguistics-Driven Acoustic Embedding Selection

no code implementations • 2 Dec 2019 • Shubhi Tyagi, Marco Nicolis, Jonas Rohnke, Thomas Drugman, Jaime Lorenzo-Trueba

Recent advances in Text-to-Speech (TTS) have improved quality and naturalness to near-human capabilities when considering isolated sentences.

Speech Synthesis Text to Speech