Text-To-Speech Data Augmentation for Low Resource Speech Recognition. (arXiv:2204.00291v1 [cs.CL])

Nowadays, the main problem of deep learning techniques used in the
development of automatic speech recognition (ASR) models is the lack of
transcribed data. The goal of this research is to propose a new data
augmentation method to improve ASR models for agglutinative and low-resource
languages. This novel data augmentation method generates both synthetic text
and synthetic audio. Some experiments were conducted using the corpus of the
Quechua language, which is an agglutinative and low-resource language. In this
study, a …

arxiv augmentation data speech speech recognition text text-to-speech