Systems and methods for adaptive text to speech for diverse styles

Abstract

Embodiments described herein provide adaptive text to speech (TTS) methods for generating voices in diverse styles is built on a pretrained TTS model and an age/gender/emotion recognition model and conditional LoRa (Low-Rank Adaptation of Large Language Models) module that is a style adaptation module. The style adaptation module generates style vectors, where a style consists of a combination of acoustic properties such as tone, speaking rate, accent, etc. These methods allow for generation of diverse voice styles, including seen and unseen styles (i.e., styles not used in the training dataset).

Dependencies are inferred from the claim text.