The present work reviews theories and empirical findings, including results from two new experiments, that bear on the perception of English vowels, with an emphasis on the comparison of data analytic "machine recognition" approaches with results from speech perception experiments. Two major sources of variability (viz., speaker differences and consonantal context effects) are addressed from the classical perspective of overlap between vowel categories in F1 x F2 space. Various approaches to the reduction of this overlap are evaluated. Two types of speaker normalization are considered. "Intrinsic" methods based on relationships among the steady-state properties (F0, F1, F2, and F3) within individual vowel tokens are contrasted with "extrinsic" methods, involving the relationships among the formant frequencies of the entire vowel system of a single speaker. Evidence from a new experiment supports Ainsworth's (1975) conclusion [W. Ainsworth, Auditory Analysis and Perception of Speech (Academic, London, 1975)] that both types of information have a role to play in perception. The effects of consonantal context on formant overlap are also considered. A new experiment is presented that extends Lindblom and Studdert-Kennedy's finding [B. Lindblom and M. Studdert-Kennedy, J. Acoust. Soc. Am. 43, 840-843 (1967)] of perceptual effects of consonantal context on vowel perception to /dVd/ and /bVb/ contexts. Finally, the role of vowel-inherent dynamic properties, including duration and diphthongization, is briefly reviewed. All of the above factors are shown to have reliable influences on vowel perception, although the relative weight of such effects and the circumstances that alter these weights remain far from clear. It is suggested that the design of more complex perceptual experiments, together with the development of quantitative pattern recognition models of human vowel perception, will be necessary to resolve these issues.

Statistical analysis of F1 and F2 measurements from nucleus and offglide sections of isolated Canadian English vowels shows significant formant frequency change not only for the ‘‘phonetic diphthongs’’ /e/ and /o/, but also for the ‘‘monophthongs’’ /ι/, /q/, and /1/. In a perceptual experiment, brief sections were extracted from ‘‘nucleus’’ and ‘‘offglide’’ portions of naturally produced vowels. Two sections from each vowel were presented to listeners in each of three conditions: (1) natural order (nucleus followed by offglide); (2) repeated nucleus (nucleus followed by itself); and (3) reverse (offglide followed by nucleus). Listeners’ error rates for the natural order condition were comparable to those for unmodified full vowels (averaging 14% and 13%, respectively). Significantly higher error rates were found for the repeated nucleus (32%) and reverse (38%) conditions. Observed confusion matrices were strongly correlated with predictions from a pattern recognition model incorporating the formant measurements. This study provides evidence for the importance of inherent spectral change in listeners’ perception of isolated vowels. In addition, the problem of the parametric representation of formant trajectories is discussed and preliminary evidence for the persistence of vowel-inherent spectral change in consonantal context is presented.

A significant body of evidence has accumulated indicating that vowel identification is influenced by spectral change patterns. For example, a large-scale study of vowel formant patterns showed substantial improvements in category separability when a pattern classifier was trained on multiple samples of the formant pattern rather than a single sample at steady state [J. Hillenbrand et al., J. Acoust. Soc. Am. 97, 3099-3111 (1995)]. However, in the earlier study all utterances were recorded in a constant /hVd/ environment. The main purpose of the present study was to determine whether a close relationship between vowel identity and spectral change patterns is maintained when the consonant environment is allowed to vary. Recordings were made of six men and six women producing eight vowels (see text) in isolation and in CVC syllables. The CVC utterances consisted of all combinations of seven initial consonants (/h,b,d,g,p,t,k/) and six final consonants (/b,d,g,p,t,k/). Formant frequencies for F1-F3 were measured every 5 ms during the vowel using an interactive editing tool. Results showed highly significant effects of phonetic environment. As with an earlier study of this type, particularly large shifts in formant patterns were seen for rounded vowels in alveolar environments [K. Stevens and A. House, J. Speech Hear. Res. 6, 111-128 (1963)]. Despite these context effects, substantial improvements in category separability were observed when a pattern classifier incorporated spectral change information. Modeling work showed that many aspects of listener behavior could be accounted for by a fairly simple pattern classifier incorporating F0, duration, and two discrete samples of the formant pattern.

The purpose of this study was to examine the role of formant frequency movements in vowel recognition. Measurements of vowel duration, fundamental frequency, and formant contours were taken from a database of acoustic measurements of 1668 /hVd/ utterances spoken by 45 men, 48 women, and 46 children [Hillenbrand et al., J. Acoust. Soc. Am. 97, 3099-3111 (1995)]. A 300-utterance subset was selected from this database, representing equal numbers of 12 vowels and approximately equal numbers of tokens produced by men, women, and children. Listeners were asked to identify the original, naturally produced signals and two formant-synthesized versions. One set of "original formant" (OF) synthetic signals was generated using the measured formant contours, and a second set of "flat formant" (FF) signals was synthesized with formant frequencies fixed at the values measured at the steadiest portion of the vowel. Results included: (a) the OF synthetic signals were identified with substantially greater accuracy than the FF signals; and (b) the naturally produced signals were identified with greater accuracy than the OF synthetic signals. Pattern recognition results showed that a simple approach to vowel specification based on duration, steady-state F0, and formant frequency measurements at 20% and 80% of vowel duration accounts for much but by no means all of the variation in listeners' labeling of the three types of stimuli.

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