## 1aSP2. Fundamental frequency estimation of speech signals using a nonlinear observer.

### Session: Monday Morning, December 2

### Time: 10:30

**Author: Taro Yoshihama**

**Location: Dept. of Electron. and Commun., Meiji Univ., 1-1-1, Higashi-Mita, Tama-ku, Kawasaki, 214 Japan**

**Author: Asako Doi**

**Location: Dept. of Electron. and Commun., Meiji Univ., 1-1-1, Higashi-Mita, Tama-ku, Kawasaki, 214 Japan**

**Author: Yoshihisa Ishida**

**Location: Dept. of Electron. and Commun., Meiji Univ., 1-1-1, Higashi-Mita, Tama-ku, Kawasaki, 214 Japan**

**Abstract:**

This paper describes a new method of estimating the fundamental frequency
of speech signals using an adaptive Fourier analysis (AFA) algorithm based on
the presumption of signal parameters using a nonlinear observer. The recursive
presumption of signal parameters such as fundamental frequency can be
effectively implemented by using the proposed AFA algorithm. Nonlinear observers
can be used to measure nonlinear parameters which are included in observed
signals. Recursive estimation procedures make it possible to follow the slow
changes of signal parameters to be measured. In real-time signal analysis, the
recursive algorithm is preferred to the conventional Fourier transformation
because of this property. The AFA algorithm, which is based on the recursive
discrete Fourier transform (RDFT), is a recursive algorithm for the simultaneous
estimation of the Fourier coefficients and instantaneous fundamental frequency
of speech signals. This AFA algorithm is applied to speech signals with an
arbitrary length of the transform window. Further efforts are required for
better convergence speed of the proposed algorithm, but this method is mostly
capable of adapting and tracking nonlinear signals such as speech sound.

ASA 132nd meeting - Hawaii, December 1996