Scalable decomposition of speech waveforms

Decomposition of speech signals into periodic and noise components is widely used in speech coding to facilitate efficient compression. Existing decomposition schemes are too inflexible to model transient changes in the speech signal, require high delay or produce a large parameter set that is not scalable to low rates. This paper proposes a technique that requires only a single frame of speech and produces a scalable decomposition. The latter allows reconstruction accuracy to be varied according to the bit rate available.