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First Steps Towards Hybrid Speech Synthesis in Czech TTS System ARTIC

机译：捷克TTS系统ARTIC迈向混合语音合成的第一步

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The hybrid speech synthesis, combining an HMM-based parameter trajectories generator and unit selection, was reported to achieve high speech output quality, in some cases even outperforming the "classic" unit selection method, while having reasonable cost of hardware requirements increase, especially when compared to modern DNN-based (e.g. WaveNet) speech synthesis methods. The present paper introduces one of this hybrid approaches, facing up the mismatch between rather smooth flow of parameters when generated by a model and between their varying evolution when obtained from speech. We also describe several modifications of target cost computation, influencing the selection of units being close to the required parameters, while our aim is to obtain a notion of the mutual interactions within the modified selection process. The overall conclusion is covered by listening tests, showing comparable quality of the trial hybrid synthesis described to unit selection method tuned through the years.
机译：据报道，混合语音合成结合了基于HMM的参数轨迹生成器和单位选择，可实现较高的语音输出质量，在某些情况下甚至优于“经典”单位选择方法，同时硬件需求的合理成本增加，尤其是当与基于DNN的现代语音合成方法（例如WaveNet）相比。本文介绍了这种混合方法中的一种，它解决了模型生成时参数平滑流动与语音获取时变化演化之间的不匹配问题。我们还描述了目标成本计算的几种修改形式，影响了接近所需参数的单位的选择，而我们的目标是获得修改后的选择过程中相互影响的概念。听力测试涵盖了总体结论，显示了与多年来调整的单位选择方法相比，所述试验混合合成的质量可比。

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