Speech parameter generation from HMM using dynamic features
Speech parameter generation from HMM using dynamic features
复制标题
DOI：
10.1109/icassp.1995.479684
复制
发表时间：
1995-05
期刊：
影响因子：
--
通讯作者：
K. Tokuda;Takao Kobayashi;S. Imai
中科院分区：
文献类型：
--
作者：
K. Tokuda;Takao Kobayashi;S. Imai
本文提出了一种基于Hertz的语音参数生成算法，该算法包含了语音的动态特征。通过引入语音的动态特征，提高了基于HHT的语音识别性能。因此，我们认为，如果有一种方法能从HHALF中提取出包含动态特征的语音参数，那么它将有助于按规则进行语音合成。它示出的参数生成从HISTORY使用的动态特性的结果在搜索最佳状态序列和求解一组线性方程组为每个可能的状态序列。我们推导出一个快速算法的解决方案的类比的RLS算法的自适应滤波。我们还展示了一个语音参数生成的例子，将动态功能的效果。
This paper proposes an algorithm for speech parameter generation from HMMs which include the dynamic features. The performance of speech recognition based on HMMs has been improved by introducing the dynamic features of speech. Thus we surmise that, if there is a method for speech parameter generation from HMMs which include the dynamic features, it will be useful for speech synthesis by rule. It is shown that the parameter generation from HMMs using the dynamic features results in searching for the optimum state sequence and solving a set of linear equations for each possible state sequence. We derive a fast algorithm for the solution by the analogy of the RLS algorithm for adaptive filtering. We also show the effect of incorporating the dynamic features by an example of speech parameter generation.