使用MARY TTS平台为资源不足的语言建立声音的逐步过程

Manuri Senarathna, K. Pulasinghe, Shyam Reyal
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引用次数: 0

摘要

本文提供了一个全面的指南,创建合成语音,以支持MaryTTS平台的资源语言。尽管研究人员在语音合成领域做出了广泛的贡献,但缺乏完整的文档阻碍了MaryTTS尚未支持的语言的语音构建过程,使文本到语音(TTS)领域知识不足的用户的实现过程复杂化。本研究中讨论的逐步过程进一步展示了为僧伽罗语创建合成语音,以单元选择作为语音构建方法。经诊断韵测试(DRT)评估,生成的僧伽罗语语音可理解性评分为91.7%。与地面真实数据的比较证明,当与相同的参与者进行测试时,其可理解性得分被确定为97.9%,这与人类语言非常接近。平均意见分数(Mean Opinion Score, MOS)显示自然度水平为2.993,与理想分数4.972相比,该系统的语音质量中等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Step-by-Step Process of Building Voices for Under Resourced Languages using MARY TTS Platform
This paper presents a comprehensive guide for creating synthetic voices to support under resourced languages for the MaryTTS platform. Although researchers have extensively contributed in the domain of speech synthesis, the lack of a thorough documentation hinders the voice building process for languages not yet supported by MaryTTS, complicating the implementation process for users with inadequate knowledge in the field of Text-to-Speech (TTS). The step-by-step process discussed in this study is further demonstrated with the creation of a synthetic voice for the Sinhala language, with unit selection as the voice building approach. A Sinhalese voice was generated with an intelligibility score of 91.7% upon evaluation with Diagnostic Rhyme Test (DRT). Comparison with ground truth data proved a close approximation to human speech where the intelligibility score was identified as 97.9%, when tested with the same participants. The Mean Opinion Score (MOS) revealed a naturalness level of 2.993, indicating a moderately high speech quality for the proposed system in comparison with the ideal score of 4.972.
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