Past results have suggested that initial strengthening (IS) effects target the contrastive phonetic properties of segments, with a maximization of acoustic contrasts in initial position of strong prosodic domains. Here, we investigate whether IS effects translate into a better acoustic discriminability within the French oral vowels system. Discriminability is assessed on the basis of classification results of two types of classifiers: a linear discriminant analysis (LDA) based on the four formants frequencies, and a deep convolutional neural network (CNN) based on spectrograms. The test set includes 720 exemplars of /i, y, e, ɛ, a, x, u, o, ɔ/ (with /x/=/ø, oe/) produced in a labial context, either in intonational phrase initial (IPi) or word initial (Wi) position. Classifiers were trained using a set of 4500 vowels extracted from a large read speech corpus. Results show a better discriminability of vowels (overall better classification rate) in IPi than in Wi with the two methods. Less confusion in IPi is found between rounded and unrounded, and between back and front vowels, but not between the vowels along the four-way height contrast. Less confusion between peripheral and central vowels also expresses a maximization of contrasts within the acoustic space in IPi position.