Comprehensive Evaluation of Statistical Speech Waveform Synthesis

Thomas Merritt, Bartosz Putrycz, Adam Nadolski, Tianjun Ye, Daniel Korzekwa, Wiktor Dolecki, Thomas Drugman, V. Klimkov, A. Moinet, A. Breen, Rafal Kuklinski, N. Strom, R. Barra-Chicote
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引用次数: 17

Abstract

Statistical TTS systems that directly predict the speech waveform have recently reported improvements in synthesis quality. This investigation evaluates Amazon’s statistical speech waveform synthesis (SSWS) system. An in-depth evaluation of SSWS is conducted across a number of domains to better understand the consistency in quality. The results of this evaluation are validated by repeating the procedure on a separate group of testers. Finally, an analysis of the nature of speech errors of SSWS compared to hybrid unit selection synthesis is conducted to identify the strengths and weaknesses of SSWS. Having a deeper insight into SSWS allows us to better define the focus of future work to improve this new technology.
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统计语音波形合成的综合评价
直接预测语音波形的统计TTS系统最近报道了合成质量的改进。本研究评估了亚马逊的统计语音波形合成(SSWS)系统。在多个领域对SSWS进行了深入评估,以更好地了解质量的一致性。通过在一组单独的测试人员中重复该过程,可以验证评估的结果。最后,对SSWS与混合单元选择合成的语音错误性质进行了分析,以确定SSWS的优缺点。对SSWS有了更深入的了解,我们可以更好地确定未来工作的重点,以改进这项新技术。
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