Grapheme-to-phoneme conversion for Chinese text-to-speech

By Jun Xu, Guohong Fu, Haizhou Li. 2004

8 citations recorded by the source corpus.

Subfields: Artificial Intelligence

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xu Tan
2. Tao Qin
3. Tie-Yan Liu
4. Frank K. Soong
5. Sheng Zhao
6. Yi Ren
7. Lei He
8. Yang Zhang

Citations in the corpus

• A Survey on Neural Speech Synthesis (2021, methodology): “Thus, G2P conversion in this kind of languages is mainly responsible for polyphone disambiguation, which decides the appropriate pronunciation based on the current word context [441, 392, 224, 295, 321, 29, 257].”
• A Unified Sequence-to-Sequence Front-End Model for Mandarin Text-to-Speech Synthesis (2019, background): “As described in [9], the main objective in Mandarin G2P is polyphone disambiguation(PD), which affect the speech quality significantly in TTS.”