Biomedical subjects

S A Zahorian

Publications and source records attributed to S A Zahorian.

3 recordsLinked to original sources

PubMed1993

Spectral-shape features versus formants as acoustic correlates for vowels.

The first three formants, i.e., the first three spectral prominences of the short-time magnitude spectra, have been the most commonly used acoustic cues for vowels ever since the work of Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)]. However, spectral shape features, which encode the global smoothed spectrum, provide a more complete spectral description, and therefore might be even better acoustic correlates for vowels. In this study automatic vowel classification experiments were used to compare formants and spectral-shape features for monopthongal vowels spoken in the context of isolated CVC words, under a variety of conditions. The roles of static and time-varying information for vowel discrimination were also compared. Spectral shape was encoded using the coefficients in a cosine expansion of the nonlinearly scaled magnitude spectrum. Under almost all conditions investigated, in the absence of fundamental frequency (F0) information, automatic vowel classification based on spectral-shape features was superior to that based on formants. If F0 was used as an additional feature, vowel classification based on spectral shape features was still superior to that based on formants, but the differences between the two feature sets were reduced. It was also found that the error pattern of perceptual confusions was more closely correlated with errors in automatic classification obtained from spectral-shape features than with classification errors from formants. Therefore it is concluded that spectral-shape features are a more complete set of acoustic correlates for vowel identity than are formants. In comparing static and time-varying features, static features were the most important for vowel discrimination, but feature trajectories were valuable secondary sources of information.

Female↗

PubMed1991

Speaker normalization of static and dynamic vowel spectral features.

Two methods are described for speaker normalizing vowel spectral features: one is a multivariable linear transformation of the features and the other is a polynomial warping of the frequency scale. Both normalization algorithms minimize the mean-square error between the transformed data of each speaker and vowel target values obtained from a "typical speaker." These normalization techniques were evaluated both for formants and a form of cepstral coefficients (DCTCs) as spectral parameters, for both static and dynamic features, and with and without fundamental frequency (F0) as an additional feature. The normalizations were tested with a series of automatic classification experiments for vowels. For all conditions, automatic vowel classification rates increased for speaker-normalized data compared to rates obtained for nonnormalized parameters. Typical classification rates for vowel test data for nonnormalized and normalized features respectively are as follows: static formants--69%/79%; formant trajectories--76%/84%; static DCTCs 75%/84%; DCTC trajectories--84%/91%. The linear transformation methods increased the classification rates slightly more than the polynomial frequency warping. The addition of F0 improved the automatic recognition results for nonnormalized vowel spectral features as much as 5.8%. However, the addition of F0 to speaker-normalized spectral features resulted in much smaller increases in automatic recognition rates.

Adult↗

PubMed1977

Vibrotactile frequency for encoding a speech parameter.

Frequency of vibration has not been widely used as a parameter for encoding speech-derived information on the skin. Where it has been used, the frequencies employed have not necessarily been compatible with the capabilities of the tactile channel, and no determination was made of the information transmitted by the frequency variable, as differentiated from other parameters used simultaneously, such as duration, amplitude, and location. However, several investigators have shown that difference limens for vibration frequency may be small enough to make stimulus frequency useful in encoding a speech-derived parameter such as the fundamental frequency of voiced speech. In the studies reported here, measurements have been made of the frequency discrimination ability of the volar forearm, using both sinusoidal and pulse waveforms. Stimulus configurations included the constant-frequency vibrations used by other laboratories as well as frequency-modulated (warbled) stimulus patterns. The frequency of a warbled stimulus was designed to have temporal variations analogous to those found in speech. The results suggest that it may be profitable to display the fundamental frequency of voiced speech on the skin as vibratory frequency, thought it might be desirable to recode fundamental frequency into a frequency range more closely matched to the skin's capability.

Acoustics↗