The acoustic manifestation of nasal murmurs is significantly context dependent. To what extent can the class of nasals be automatically detected without prior detailed knowledge of the segmental context? This contribution reports on the characterization of the spectral change accompanying the transition between vowel and nasal for the purpose of automatic detection of nasal murmurs. The speech is first segmented into syllable‐sized units, the voiced sonorant region within the syllable is delimited, and the points of maximal spectral change on either side of the syllabic peak are hypothesized to be potential nasal transitions. Four simply extractible acoustic parameters, the relative energy change in the frequency bands 0–1, 1–2, and 2–5 kHz, and the frequency centroid of the 0–500‐Hz band at four points in time spaced 12.8 msec apart are used to represent the dynamic transition. Categorization of the transitions using multivariate statistics on some 524 transition segments from data of two speakers resulted in a 91% correct nasal/non‐nasal decision rate.