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Robust Rule-Based Method for Automatic Break Assignment in Russian Texts

机译:基于俄罗斯文本中的自动破坏分配的强大规则方法

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In this paper a new rule-based approach to break assignment for the Russian language is discussed. It is a flexible and robust method of segmentation of texts in Russian in prosodic units. We implemented it in the recent "Orator" text-to-speech (TTS) system. The model was developed to use for the inflective languages as an alternative both for statistic and for strict rule-based algorithms. It is designed in such a way that all potentially tunable context dependencies are brought up to the interface grammar and can be easily modified by linguists. The algorithm we developed performs well on different kinds of texts due to this simple and intuitive grammar built upon an elaborate mechanism of morpho-grammatical analysis. Juncture correct rate varies between more than 98% for simple literary texts and 85% for raw transcripts of spontaneous speech.
机译:本文讨论了一种新的基于规则的俄语分配的方法。它是俄罗斯罗布吉特单位中俄语细分的灵活性和强大的方法。我们在最近的“演讲”文本到语音(TTS)系统中实现了它。该模型是开发的,用于将流入语言作为统计和严格的规则算法的替代品。它以这样的方式设计,即所有潜在的可调上下文依赖关系都会被带到界面语法,可以通过语言学家轻松修改。由于这种简单而直观的语法构建了在Morpho-Schamication分析的机制之上,我们开发的算法在不同类型的文本上表现良好。随着自发言论的原始成绩单,即表示正确的速率在98%之间有超过98%。

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