Aliasing Reduction for Modified Discrete Cosine Transform Domain Filtering and its Application to Speech Enhancement

Efficient combinations of coding and manipulation of audio signals in the spectral domain are often desirable in communication systems. The modified discrete cosine transform (MDCT) represents a popular spectral transform in audio coding as it leads to compact signal representations. However, as the MDCT corresponds to a critically sampled filter bank, it is in general not appropriate to directly apply it to filtering tasks. In this paper we present a method to compensate for aliasing terms that arise from such direct MDCT domain filtering. The discussion is thereby based on a rigorous matrix representation of critically sampled filter banks which also leads to corresponding efficient realizations. As an application showcase, noise reduction for MDCT based speech coding is considered in simulations.