Pitch、Energy、Speech rate、Formant and Mel sub-band energy etc related statistic features are extracted from speech signal.
从语音信号中提取了基于基音频率、振幅能量、语速和共振峰和Mel频带子带能量等相关的统计特征参数。
参考来源 - 基于独立分量分析的语音情感识别研究·2,447,543篇论文数据，部分数据来源于NoteExpress
通过改变相应的语音参数可以灵活地调节音节的时长、基音频率和音强。
The duration and fundamental frequency can be changed by adjusted the speech parameters.
MFCC参数主要描述了表征声道特性的谱包络特征，而忽略了基音频率对它的影响。
MFCC parameters is main describes the spectrum envelope features, which is used to state the vacal track characterizatics, while ignoring the impact of pitch frequency.
通过修改基音频率和共振峰结构，该方法合成的语音有效地模拟了目标说话人的特性。
The modification of both pitch and formant structure contributed greatly to reproducing the target speaker's characteristics.
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