一种对汉语孤立字词进行声韵分割的时频方法

Time-frequency method for Chinese monosyllable and dual-syllable intial-final segmentation

正确的声韵分离是汉语语音识别与合成等的基础和关键。针对传统声韵分割中,时域短时能量和过零率容易受到噪声干扰从而导致分割不准确的问题,结合语谱图所体现的时频信息对汉语孤立字进行了声韵分割,并进一步对信号进行经验模态分解和计算保号率,实现了一种对二字词的时频声韵分割方法。仿真实验结果显示,该方法对汉语孤立字和二字词的分割准确率分别达到了86.92%和77.47%。

Accurate initial-final segmentation is considered as a basis and key work for Chinese speech recognition and synthesis etc. Since short-time energy and zero cross rate which are used in traditional segmentation are easily disturbed by noises and cause further segmentation error, spectrogram is introduced here to Chinese monosyllable initial-final segmentation due to its time-frequency information. It is proved to be effective by experiment, it is then combined with empirical mode decomposition and keeping-sign-ratio computing in Chinese dual-syllable initial-final segmentation. As is shown in experiment, the proposed time-frequency method has achieved an accuracy of 86.92% and 77.47% in the initial-final segmentation for Chinese monosyllable and dual-syllable respectively.