  While recent advances in Text-To-Speech synthesis have yielded remarkable
improvements in generating high-quality speech, research on lightweight and
fast models is limited. This paper introduces FLY-TTS, a new fast, lightweight
and high-quality speech synthesis system based on VITS. Specifically, 1) We
replace the decoder with ConvNeXt blocks that generate Fourier spectral
coefficients followed by the inverse short-time Fourier transform to synthesize
waveforms; 2) To compress the model size, we introduce the grouped
parameter-sharing mechanism to the text encoder and flow-based model; 3) We
further employ the large pre-trained WavLM model for adversarial training to
improve synthesis quality. Experimental results show that our model achieves a
real-time factor of 0.0139 on an Intel Core i9 CPU, 8.8x faster than the
baseline (0.1221), with a 1.6x parameter compression. Objective and subjective
evaluations indicate that FLY-TTS exhibits comparable speech quality to the
strong baseline.
