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Time–Frequency Cepstral Features And Heteroscedastic Linear Discriminant Analysis For Language Recognition, Wei-Qiang Zhang, Liang He, Yan Deng, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Research and Publications

The shifted delta cepstrum (SDC) is a widely used feature extraction for language recognition (LRE). With a high context width due to incorporation of multiple frames, SDC outperforms traditional delta and acceleration feature vectors. However, it also introduces correlation into the concatenated feature vector, which increases redundancy and may degrade the performance of backend classifiers. In this paper, we first propose a time-frequency cepstral (TFC) feature vector, which is obtained by performing a temporal discrete cosine transform (DCT) on the cepstrum matrix and selecting the transformed elements in a zigzag scan order. Beyond this, we increase discriminability through a heteroscedastic …