Overview
FastSpeech2 is a neural network architecture for text-to-speech (TTS) synthesis developed by Microsoft. It addresses the speed and stability issues of previous autoregressive TTS models. FastSpeech2 utilizes a feed-forward transformer network trained with knowledge distillation to achieve significantly faster synthesis speeds. The model includes a variance adaptor that predicts pitch, energy, and duration from text, enabling fine-grained control over speech characteristics. The architecture consists of an encoder, a variance adaptor, and a decoder. The encoder transforms text into a latent representation, which is then modulated by the variance adaptor. Finally, the decoder synthesizes the speech waveform. It's designed for research and development purposes, offering a high-performance, customizable TTS solution. Use cases include generating synthetic voices for virtual assistants, creating audiobooks, and developing accessible communication tools for individuals with speech impairments.