  The few-shot multi-speaker multi-style voice cloning task is to synthesize
utterances with voice and speaking style similar to a reference speaker given
only a few reference samples. In this work, we investigate different speaker
representations and proposed to integrate pretrained and learnable speaker
representations. Among different types of embeddings, the embedding pretrained
by voice conversion achieves the best performance. The FastSpeech 2 model
combined with both pretrained and learnable speaker representations shows great
generalization ability on few-shot speakers and achieved 2nd place in the
one-shot track of the ICASSP 2021 M2VoC challenge.
