A model for nonstationary analysis of speech

The analysis of speech for high-quality recognition or for coding is usually done by using a short-time interval for a time-invariant model, where local stationarity is assumed. We propose a general framework for applying a linear, time-varying model to the speech analysis problem. A key feature in our derivation is the assumption that the instantaneous frequency response of the time-varying vocal tract can be represented as a linear combination of appropriately frequency-shifted versions of a single basis function. Both time- and frequency- domain models for the speech signal are derived, Also, a statistic is derived which indicates the transient behavior of the signal and which might be used to arrive at a constant entropy signal analysis methodology. This is a first report of on going theoretical and experimental research.