1 citations · 1 across the 3 of their papers we have counts for
3 papers
BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization
Henry B. Moss, Vatsal Aggarwal, Nishant Prateek +2
We present BOFFIN TTS (Bayesian Optimization For FIne-tuning Neural Text To Speech), a novel approach for few-shot speaker adaptation. Here, the task is to fine-tune a pre-trained…
Using VAEs and Normalizing Flows for One-shot Text-To-Speech Synthesis of Expressive Speech
Vatsal Aggarwal, Marius Cotescu, Nishant Prateek +2
We propose a Text-to-Speech method to create an unseen expressive style using one utterance of expressive speech of around one second. Specifically, we enhance the disentanglement…
In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data
Nishant Prateek, Mateusz Łajszczak, Roberto Barra-Chicote +5
Neural text-to-speech synthesis (NTTS) models have shown significant progress in generating high-quality speech, however they require a large quantity of training data. This makes…