  Current end-to-end code-switching Text-to-Speech (TTS) can already generate
high quality two languages speech in the same utterance with single speaker
bilingual corpora. When the speakers of the bilingual corpora are different,
the naturalness and consistency of the code-switching TTS will be poor. The
cross-lingual embedding layers structure we proposed makes similar syllables in
different languages relevant, thus improving the naturalness and consistency of
generated speech. In the end-to-end code-switching TTS, there exists problem of
prosody instability when synthesizing paragraph text. The text enhancement
method we proposed makes the input contain prosodic information and
sentence-level context information, thus improving the prosody stability of
paragraph text. Experimental results demonstrate the effectiveness of the
proposed methods in the naturalness, consistency, and prosody stability. In
addition to Mandarin and English, we also apply these methods to Shanghaiese
and Cantonese corpora, proving that the methods we proposed can be extended to
other languages to build end-to-end code-switching TTS system.
