Vowel characterization of Spanish speakers from Antioquia–Colombia using a specific-parameterized discrete wavelet transform analysis

•A discrete wavelet transform based analysis for vowel formants extraction is presented.•The wavelets parameters are exploited to establish a vowel-specific analysis.•The achieved formants distribution can be well characterized by a simple classification algorithm.•The wavelet analysis combined with the classifier can be easily implemented in real-time applications. Vowel formants provide information as to how a vowel is uttered. Formant frequencies are relevant in applications involving human speech processing. However, such implementations are mainly performed with non-Spanish speakers. Thus, the Spanish vowels characterization should be further explored. In this study, a method for formants extraction based on the discrete wavelet transform is presented. The work focuses on Spanish speakers from Antioquia, Colombia. The parameters of the wavelet analysis are adjusted in order to establish a suitable vowels characterization within the frequency formant space. The results show that the vowel-specific wavelet analysis yields well defined clusters in the formant space. A k-means algorithm was trained in order to obtain representative centroids for each vowel. These centroids are tested in a vowels identification task, with good performance results. Moreover, the centroids are compared with vowel formants from Spanish speakers reported in the literature. The comparison reveals that speakers from distinct regions express specific features of vowels utterance, suggesting that speakers from regional populations within countries, can be better characterized. The proposed wavelet parametrization combined with the clustering algorithm can be attractive for real-time applications of voice processing. Furthermore, the proposed methodology can be applied in future studies with speakers from other Colombian- and Spanish-speaking regions.