2020暴雪挑战赛的OPPO系统

Yang Song, Min-Siong Liang, Guilin Yang, Kun Xie, Jie Hao
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引用次数: 0

摘要

本文介绍了暴雪挑战赛2020的OPPO文本转语音系统。基于统计参数的语音合成系统在前端和后端进行了改进。对于普通话任务,前端使用BERT模型,后端使用Tacotron声学模型和WaveRNN声码器模型。对于上海话任务,前端是从头开始构建的,后端使用了Tacotron声学模型和MelGAN声码器模型。对于普通话任务,评估结果表明,我们提出的系统在自然度方面表现最好,在相似度方面取得了接近最佳的结果。对于上海人任务,我们在大多数指标上都取得了较差的成绩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The OPPO System for the Blizzard Challenge 2020
This paper presents the OPPO text-to-speech system for Blizzard Challenge 2020. A statistical parametric speech synthesis based system was built with improvements in both frontend and backend. For the Mandarin task, a BERT model was used for the frontend, a Tacotron acoustic model and a WaveRNN vocoder model were used for the backend. For the Shanghainese task, the frontend was built from scratch, a Tacotron acoustic model and a MelGAN vocoder model were used for the backend. For the Mandarin task, evaluation results showed that our proposed system performed best in naturalness, and achieved near-best results in similarity. For the Shanghainese task, we got poor results in most indicators.
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