Conventional methods for incorporating temporal information into speech features apply regression to a series of successive cepstral vectors to generate differential cepstra, or apply a cosine transform to generate cepstral-time matrices. This paper aims to generalise these techniques such that a series of stacked cepstral vectors is multiplied by a temporal transform matrix to produce the final speech feature. This can made to incorporate both static and dynamic speech information. Using this

more »

... ethod, the coding of temporal information is not restricted to regression or cosine coefficients -any suitable transform may used. Results are presented for a variety of transforms, such as Legendre, Karhunen-Loeve, Cosine, Rectangle, where it is shown that the transform based techniques offer higher performance than conventional differential cepstrum.