The Ajmide Text-To-Speech System for Blizzard Challenge 2020

Beibei Hu, Zilong Bai, Qiang Li
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Abstract

This paper presents the Ajmide team’s text-to-speech system for the task MH1 of Blizzard Challenge 2020. The task is to build a voice from about 9.5 hours of speech from a male native speaker of Mandarin. We built a speech synthesis system in an end-to-end style. The system consists of a BERT-based text front end that process both Chinese and English texts, a multi-speaker Tacotron2 model that converts the phoneme and linguistic feature sequence into mel spectrogram, and a modified WaveRNN vocoder that generate the audio waveform from the mel spectrogram. The listening evaluation results show that our system, identified by P, performs well in terms of naturalness, intelligibility and the aspects of intonation, emotion and listening effort.
2020暴雪挑战赛的Ajmide文本转语音系统
本文介绍了Ajmide团队为暴雪挑战赛2020 MH1任务设计的文本转语音系统。这项任务是根据一个以普通话为母语的男性大约9.5小时的讲话来构建一个声音。我们建立了一个端到端的语音合成系统。该系统包括一个基于bert的文本前端,处理中英文文本,一个多扬声器Tacotron2模型,将音素和语言特征序列转换为mel谱图,以及一个改进的WaveRNN声码器,从mel谱图生成音频波形。听力评价结果表明,我们的系统在自然度、可理解性、语调、情感和听力努力等方面表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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