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Speech Synthesis Using a Non-maximally Decimated Filter Bank for Embedded Systems

机译:使用非最大抽取滤波器组的嵌入式系统语音合成

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A novel speech waveform generation method using a non-maximally decimated filter bank is proposed, where spectral features of synthetic sounds are created by amplitude modification of subband samples that are pre-decomposed from impulse or noise waveforms. The proposed method uses two synthesis banks of the maximally decimated pseudo quadrature mirror filter (QMF) bank structure which is similar to that in the MPEG audio decoder. Consequently, the computational complexity of the proposed method is O(logN) per sample, while that of the conventional method based on the source-filter model with an auto-regressive (AR) filter or mel log spectrum approximation (MLSA) filter is O(N) per sample. A MOS test for resynthe-sized speech sounds from the results of analyzing natural speech sounds showed the proposed method achieved scores similar to those of the conventional method using the MLSA filter for a female narrator.
机译:提出了一种使用非最大抽取滤波器组的新型语音波形生成方法,该方法通过对由脉冲或噪声波形预先分解的子带样本进行幅度修改来创建合成声音的频谱特征。所提出的方法使用了最大抽取伪伪正交镜像滤波器(QMF)库结构的两个合成库,这与MPEG音频解码器中的库相似。因此,所提出的方法的计算复杂度为每个样本O(logN),而基于源滤波器模型的带有自回归(AR)滤波器或梅尔对数谱近似(MLSA)滤波器的常规方法的计算复杂度为O。 (N)每个样品。根据对自然语音的分析结果,对重新合成大小的语音进行的MOS测试表明,该方法所获得的分数与使用MLSA过滤器的女性旁白者的常规分数相近。

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