All-pole modeling of speech based on the minimum variance distortionless response spectrum
All-pole modeling of speech based on the minimum variance distortionless response spectrum
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DOI：
10.1109/89.841206
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发表时间：
1997-11
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影响因子：
--
通讯作者：
M. Murthi;B. Rao
中科院分区：
文献类型：
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作者：
M. Murthi;B. Rao
基于最小方差无失真响应(MVDR)谱，我们建立了更完整的语音全极点模型。结果表明，MVDR模型提供了一类全极点模型，可以灵活地处理各种语音建模目标。特别是，高阶MVDR频谱为所有类型的语音提供了稳健的模型，包括浊音、清音和混合频谱。此外，它获得简单，并且总是优于线性预测(LP)谱。由于其高质量的建模，高阶MVDR谱适合用作高质量的参考谱，或用于语音识别等应用。此外，MVDR模式还具有开发适合于压缩应用的低阶全极点模式的灵活性。特别是，降阶MVDR全极点模型在对所有类型的语音频谱进行建模时往往优于传统的LP滤波器。为了在频域中更准确地对一组语音频谱样本进行建模，MVDR建模有助于开发更优的加权全极点滤波器。
We develop more fully all-pole modeling of speech based on the minimum variance distortionless response (MVDR) spectrum. It is shown that MVDR modeling provides a class of all-pole models that are flexible for tackling a wide variety of speech modeling objectives. In particular the high order MVDR spectrum provides a robust model for all types of speech including voiced speech, unvoiced speech, and mixed spectra. Furthermore, it is simply obtained, and is always superior to the linear prediction (LP) spectrum. With its high quality modeling, the high order MVDR spectrum is suitable for use as a high quality reference spectrum, or for applications like speech recognition. In addition, the MVDR model possesses flexibility for developing low order all-pole models suitable for compression applications. In particular; reduced order MVDR all-pole models are shown to often outperform conventional LP filters in modeling all types of speech spectra. For more accurate modeling of a set of speech spectral samples in the frequency domain, MVDR modeling facilitates the development of superior weighted all-pole filters.