DCT-based processing of dynamic features for robust speech recognition

In this paper, we explore the various properties of cepstral time coefficients (CTC) in speech recognition, and then propose several methods to refine the CTC construction process. It is found that CTC are the filtered version of mel-frequency cepstral coefficients (MFCC), and the used filters are from the discrete cosine transform (DCT) matrix. We modify these DCT-based filters by windowing, removing DC gain, and varying the filter length. The speech recognition task using Aurora-2 digit database show that the proposed methods can enhance the original CTC in improving the recognition accuracy. The resulting relative error reduction is around 20%.