  This paper describes the AS-NU systems for two tracks in MultiSpeaker
Multi-Style Voice Cloning Challenge (M2VoC). The first track focuses on using a
small number of 100 target utterances for voice cloning, while the second track
focuses on using only 5 target utterances for voice cloning. Due to the serious
lack of data in the second track, we selected the speaker most similar to the
target speaker from the training data of the TTS system, and used the speaker's
utterances and the given 5 target utterances to fine-tune our model. The
evaluation results show that our systems on the two tracks perform similarly in
terms of quality, but there is still a clear gap between the similarity score
of the second track and the similarity score of the first track.
