  In this paper, we present a cross-lingual voice cloning approach. BN features
obtained by SI-ASR model are used as a bridge across speakers and language
boundaries. The relationships between text and BN features are modeled by the
latent prosody model. The acoustic model learns the translation from BN
features to acoustic features. The acoustic model is fine-tuned with a few
samples of the target speaker to realize voice cloning. This system can
generate speech of arbitrary utterance of target language in cross-lingual
speakers' voice. We verify that with small amount of audio data, our proposed
approach can well handle cross-lingual tasks. And in intra-lingual tasks, our
proposed approach also performs better than baseline approach in naturalness
and similarity.
