Pitch is an important feature of speech. Therefore, extraction of pitch becomes a vital task for processes like speaker coding, speaker recognition, speech synthesis, speech recognition and many such applications. The few available algorithms such as Discrete Cosine Transform (DCT) based pitch extraction, harmonic product spectrum (HPS) which is obtained from DCT are useful for extraction of pitch. In this paper, we propose a hybrid Discrete Wavelet Transform-Discrete Cosine Transform (DWT- DCT HPS) based pitch extraction. A voice sample is taken and de-segmented into 36 bands in the frequency domain. Then on those bands spatial domain transformation is performed to get the most prominent features. The Gross pitch error (GPE) and Fine pitch error (FPE) criteria is used as a measure to find the accuracy of the novel method. The result depicts that the novel proposed Hybrid method is better as compared to DCT-HPS in terms of Pitch error.

音调是语音的重要特征。因此，对于诸如说话者编码，说话者识别，语音合成，语音识别以及许多此类应用的处理，音调的提取成为至关重要的任务。很少有可用的算法，例如基于离散余弦变换（DCT）的基音提取，从DCT获得的谐波乘积谱（HPS）可用于基音提取。在本文中，我们提出了一种基于离散小波变换-离散余弦变换（DWT-DCT HPS）的基音提取方法。采集语音样本并将其在频域中细分为36个频段。然后，在这些频段上执行空间域变换，以获取最突出的特征。粗节距误差（GPE）和细节距误差（FPE）准则被用作一种度量，以找到该新方法的准确性。