Locus equations were investigated as a potential metric capable of illustrating relational invariance for place of articulation in voiced initial stop consonants independently of vowel context. Locus equations are straight line regression fits to data points formed by plotting onsets of F2 transitions along the y axis and their corresponding midvowel nuclei along the x axis. Twenty subjects, 10 male and 10 female, produced/b/v/t/,/d/v/t/, and/g/v/t/tokens for ten vowel contexts. Each CVC token was repeated in a carrier phrase five times yielding 50 tokens per stop place category. Formant measures were obtained using the MacSpeech Lab II speech analysis system. Extremely linear regression functions were found characterized by distinct slopes and y intercepts as a function of place of articulation. A discriminant analysis using F2onse t and vowel frequencies as predictors showed 82%, 78%, and 67% classification rates for labial, alveolar, and velar place. Using derived slope and y-intercept values as predictors led to 100% classification into stop place categories. A neurobiologically oriented perspective on the invariance issue is developed and a brain-based recognition algorithm for stop place integrating burst and F2 trajectory cues is offered. PACS numbers: 43.71.Es, 43.71.Pc, 43.71.An INTRODUCTIONThe nature of the linguistic entity known as the "phonetic segment" and its higher-order abstraction, the "phonemic category," has long resisted an explicit specification in terms ofinstantiation in the speech signal, and ultimately, its form as a mental representation in the brain. There is even controversy as to whether linguistic units are abstract constructs (Repp, 1981; Hammarberg, 1976), or acoustic-based physical constructs possessing neurobiological reality (Sussman, 1988(Sussman, , 1989. The theoretical difficulty in accounting for the phoneme is due to its lack of transparency in the signal. The differences between a "planned segment" and an "uttered segment," as described by MacNeilage and Ladefoged (1976), succinctly capture this dilemma. The former is envisioned as discrete, static, and context-free, while the latter is characterized as overlapped, dynamic, and contextsensitive. The pervasive coarticulatory nature of speech has contributed to this theoretical puzzle known as the "noninvariance problem"--i.e., perceptual constancy despite physical variation in the signal. The "litmus test" for invariance is place of articulation in stop consonant + vowel utterances as they typify the coarticulated nature of speech.The overall purpose of this research was to present a refocused conceptualization of a traditional, but elusive, candidate for acoustic invariance for place of articulation-the second formant transition as its onset and trajectory vary with the following vowel. The departure point was to seek invariant acoustic patterns related to place of articulation, not for each individual token, but rather for an entire phonemic category. A. Searching for invariance: formant transitionsPerhaps the earliest w...

Neuroethological investigations of mammalian and avian auditory systems have documented species-specific specializations for processing complex acoustic signals that could, if viewed in abstract terms, have an intriguing and striking relevance for human speech sound categorization and representation. Each species forms biologically relevant categories based on combinatorial analysis of information-bearing parameters within the complex input signal. This target article uses known neural models from the mustached bat and barn owl to develop, by analogy, a conceptualization of human processing of consonant plus vowel sequences that offers a partial solution to the noninvariance dilemma – the nontransparent relationship between the acoustic waveform and the phonetic segment. Critical input sound parameters used to establish species-specific categories in the mustached bat and barn owl exhibit high correlation and linearity due to physical laws. A cue long known to be relevant to the perception of stop place of articulation is the second formant (F2) transition. This article describes an empirical phenomenon – the locus equations – that describes the relationship between the F2 of a vowel and the F2 measured at the onset of a consonant-vowel (CV) transition. These variables, F2 onset and F2 vowel within a given place category, are consistently and robustly linearly correlated across diverse speakers and languages, and even under perturbation conditions as imposed by bite blocks. A functional role for this category-level extreme correlation and linearity (the “orderly output constraint”) is hypothesized based on the notion of an evolutionarily conserved auditory-processing strategy. High correlation and linearity between critical parameters in the speech signal that help to cue place of articulation categories might have evolved to satisfy a preadaptation by mammalian auditory systems for representing tightly correlated, linearly related components of acoustic signals.

Locus equations were investigated as a potential higher-order metric capable of illustrating relational invariance for place of articulation in voiced initial stop consonants independently of vowel context. Locus equations are straight-line regression fits to data points formed by plotting onsets of F2 transitions along the y axis and their corresponding midvowel nuclei along the x axis. Twenty subjects, 10 male and 10 female, produced /b/v/t/, /d/v/t/, and /g/v/t/ tokens for 10 vowel contexts. Each CVC token was repeated in a carrier phrase five times yielding 150 tokens per subject. Formant measures were obtained using the MacSpeech Lab II speech analysis system. Locus equation scatter-plots revealed extremely tight clustering of points around the regression line that were consistent across speakers and gender. Derived slope and y-intercept parameters were significantly different across stop place categories. The relative value of F2onset as it linearly changes in relation to the coarticulatorily produced vowel reflects an acoustic correlate of relational invariance for stop place. A discriminant analysis using F2onset & vowel as predictors showed 82%, 78%, and 67% classification rates for labial, alveolar, and velar place. Using derived slope and y-intercept values as predictors led to 100% classification into stop place categories. A neurobiologically oriented perspective on the invariance issue is explored and a brain-based recognition algorithm for stop place integrating burst and F2 cues is offered. [Work supported by NSF.]

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A previous study [H. Sussman, H. McCaffrey, and S. Matthews, J. Acoust. Soc. Am. 90, 1309-1325 (1991)] of American English CV coarticulation showed a remarkably linear relationship between onset frequencies of F2 transitions, plotted on the y axis, in relation to the F2 midvowel "target" frequencies, plotted on the x axis, for CVC tokens with initial [b d g] and ten medial vowel contexts. Slope and y-intercept values of regression functions fit to these scatterplots ("locus equations") were shown to serve as statistically powerful phonetic descriptors of place of articulation. The present study extends the locus equation metric to three additional languages--Thai, Cairene Arabic, and Urdu--having both two and four place contrasts for syllable-initial voiced stops. A total of 14 speakers (Thai = 6, Arabic = 3, Urdu = 5) produced 1740 CVC tokens that were acoustically analyzed using MacSpeech Lab II. Strong linear regression relationships were found for every stop category across all speakers. Slopes and y intercepts systemically varied as a function of place of articulation. Cross-language comparisons of stop place categories were performed but variability of slope and y intercept means tempered conclusions concerning the existence of CV "phonetic hot spots."