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Singing-voice synthesis using demi-syllable unit selection

机译:使用半音节单元选择的歌声合成

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In this study, an algorithm having a nice dynamic-programming structure is proposed for unit selection. This algorithm considers the costs of pitch and duration transformations, and the costs of contextual and spectral discontinuities. Here, the voice unit, demi-syllable, is adopted. In the training phase, each demi-syllable unit is analyzed to obtain a sequence of discrete cepstral coefficient (DCC) vectors. Then, in the synthesis phase, the pitch and duration of a syllable can be adjusted. In addition, the singing voice signals are synthesized with harmonic plus noise model (HNM). To evaluate the performance of our unit selection algorithm, we have conducted two listening tests. One test is to evaluate the spectral fluency (continuity), and another test is to evaluate the synthesized songs' quality. The results of both tests show that our algorithm can improve a synthesized song's fluency level and quality noticeably.
机译:在这项研究中,提出了一种具有良好动态编程结构的算法用于单位选择。该算法考虑了音高和持续时间转换的成本,以及上下文和频谱不连续性的成本。在此,采用半音节音节的语音单元。在训练阶段,将对每个半音节音节单元进行分析,以获得一系列离散倒谱系数(DCC)向量。然后,在合成阶段,可以调节音节的音调和持续时间。此外,歌声信号通过谐波加噪声模型(HNM)进行合成。为了评估单元选择算法的性能,我们进行了两次听觉测试。一个测试是评估频谱的流畅性(连续性),另一个测试是评估合成歌曲的质量。两种测试的结果表明,我们的算法可以显着提高合成歌曲的流利程度和质量。

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