## 2pSPb6. Vowel identification from harmonic contours of vowel centers using an automatic algorithm that eliminates windowing error.

### Session: Tuesday Afternoon, May 14

### Time: 3:30

**Author: Octavio Betancourt**

**Author: John Antrobus**

**Location: Depts. of Comput. Sci. and Psych., City College of the City Univ. of New York, New York, NY 10031**

**Abstract:**

Using successive nonoverlapping 22.5-ms windows, 16-kHz sampling, no
filtering, an automatic algorithm locates five successive windows of minimum
spectral velocity, describes a subwindow equal to some multiple of the natural
period of F[inf 0], and maps the subwindow onto the unit circle, the interval 0,
2(pi). Consequently, the Fourier analysis is performed on a window where the
signal is exactly periodic. Because the spectrum contains no extraneous
numerical sidebands it is precise, and consists only of natural harmonics in the
acoustic signal. The first 32-integer multiples of F[inf 0] are sufficient to
describe the spectrum. J. D. Miller's [J. Acoust. Soc. Am. 85, 2114--2134
(1989)] log F[inf 0][sup 1/3] shift increases recognition of 12 vowels (men,
women, and children) in the Hillenbrand et al. [J. Acoust. Soc. Am. 97,
3099--3111 (1995)] data set from 52% to 75% using a Euclidean classifier
(EC---with jackknife). Cosine series (12) were used to compare our Betancourt
spectrum (EC: 76%) with the Hamming window (EC: 61%). Quadratic discriminant
function analysis + log F[inf 0] (79%) adds only 3% to our best EC result. With
this spectrum and a log F[inf 0][sup 1/3] shift, most vowel information is
clearly captured by a simple EC.

from ASA 131st Meeting, Indianapolis, May 1996